Y 
Name  Schema Table  Database  Description  Type  Length  Unit  Default Value  Unified Content Descriptor 
y 
allwise_sc2 
WISE 
Unit sphere position y value 
float 
8 



y 
combo17CDFSSource 
COMBO17 
ycoordinate on image cdfs_r.fit 
real 
4 
pix 


y 
vhsDetection 
VHSDR2 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSDR3 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSDR4 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSDR6 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20120926 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20130417 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20140409 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20150108 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20160114 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20160507 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20170630 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection 
VHSv20180419 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vhsDetection, vhsListRemeasurement 
VHSDR1 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoDetection 
VIDEODR2 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoDetection 
VIDEODR3 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoDetection 
VIDEODR4 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoDetection 
VIDEODR5 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoDetection 
VIDEOv20100513 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoDetection 
VIDEOv20111208 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
videoListRemeasurement 
VIDEOv20100513 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGDR2 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGDR3 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGDR4 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20111019 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20130417 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20140402 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20150421 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20151230 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20160406 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20161202 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20170715 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection 
VIKINGv20181012 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingDetection, vikingListRemeasurement 
VIKINGv20110714 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingMapRemeasurement 
VIKINGZYSELJv20160909 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vikingMapRemeasurement 
VIKINGZYSELJv20170124 
Y coordinate of detection (SE: Y_IMAGE) {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCDR1 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCDR2 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCDR3 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCDR4 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20110909 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20120126 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20121128 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20130304 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20130805 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20140428 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20140903 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20150309 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20151218 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20160311 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20160822 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20170109 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20170411 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20171101 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20180702 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection 
VMCv20181120 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vmcDetection, vmcListRemeasurement 
VMCv20110816 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y 
vvvDetection 
VVVDR4 
Y coordinate of detection {catalogue TType keyword: Y_coordinate} Intensityweighted isophotal centreofgravity in Y. 
real 
4 
pixels 

pos.cartesian.y;instr.plate 
y_1eNum 
vvvPsfDophotZYJHKsMergeLog 
VVVDR4 
the extension number of this 1st epoch Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
y_1mfID 
vvvPsfDophotZYJHKsMergeLog 
VVVDR4 
the UID of the relevant 1st epoch Y tile multiframe 
bigint 
8 


meta.id;obs.field;em.IR.NIR 
y_1Mjd 
vvvPsfDophotZYJHKsMergeLog 
VVVDR4 
the MJD of the 1st epoch Y tile multiframe 
float 
8 


time;em.IR.NIR 
y_2eNum 
vvvPsfDophotZYJHKsMergeLog 
VVVDR4 
the extension number of this 2nd epoch Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
y_2mfID 
vvvPsfDophotZYJHKsMergeLog 
VVVDR4 
the UID of the relevant 2nd epoch Y tile multiframe 
bigint 
8 


meta.id;obs.field;em.IR.NIR 
y_2Mjd 
vvvPsfDophotZYJHKsMergeLog 
VVVDR4 
the MJD of the 2nd epoch Y tile multiframe 
float 
8 


time;em.IR.NIR 
Y_BJ 
grs_ngpSource, grs_ranSource, grs_sgpSource 
TWODFGRS 
Plate y_bj in 8 micron pixels 
real 
4 



y_coadd 
twomass_xsc 
TWOMASS 
y (inscan) position (coadd coord.). 
real 
4 
arcsec 

pos.cartesian;instr.det 
Y_IMAGE 
mgcDetection 
MGC 
Object y position 
real 
4 
pixel 


Y_OFF 
mgcGalaxyStruct 
MGC 
Y offset of Galaxy Centre 
real 
4 

99.99 

Y_OFFm 
mgcGalaxyStruct 
MGC 
Y offset error () 
real 
4 

99.99 

Y_OFFp 
mgcGalaxyStruct 
MGC 
Y offset error (+) 
real 
4 

99.99 

Y_R 
spectra 
SIXDF 
y position of object from R frame 
int 
4 



Y_V 
spectra 
SIXDF 
y position of object from V frame 
int 
4 



yAmpl 
vmcCepheidVariables 
VMCDR4 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20160311 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20160822 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20170109 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20170411 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20171101 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20180702 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmpl 
vmcCepheidVariables 
VMCv20181120 
PeaktoPeak amplitude in Y band {catalogue TType keyword: A(Y)} 
real 
4 
mag 
0.9999995e9 
src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCDR4 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20160311 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20160822 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20170109 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20170411 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20171101 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20180702 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAmplErr 
vmcCepheidVariables 
VMCv20181120 
Error in PeaktoPeak amplitude in Y band {catalogue TType keyword: e_A(Y)} 
real 
4 
mag 
0.9999995e9 
stat.error;src.var.amplitude;em.IR.NIR 
yAperJky3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Default point source Y aperture corrected (2.0 arcsec aperture diameter) calibrated flux If in doubt use this flux estimator 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJky3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Default point source Y aperture corrected (2.0 arcsec aperture diameter) calibrated flux If in doubt use this flux estimator 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJky3Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in default point/extended source Y (2.0 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
stat.error 
yAperJky3Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in default point/extended source Y (2.0 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
stat.error 
yAperJky4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Point source Y aperture corrected (2.8 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJky4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Point source Y aperture corrected (2.8 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJky4Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in point/extended source Y (2.8 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
stat.error 
yAperJky4Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in point/extended source Y (2.8 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
stat.error 
yAperJky6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Point source Y aperture corrected (5.7 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJky6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Point source Y aperture corrected (5.7 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJky6Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in point/extended source Y (5.7 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
stat.error 
yAperJky6Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in point/extended source Y (5.7 arcsec aperture diameter) calibrated flux 
real 
4 
jansky 
0.9999995e9 
stat.error 
yAperJkyNoAperCorr3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Default extended source Y (2.0 arcsec aperture diameter, but no aperture correction applied) aperture calibrated flux If in doubt use this flux estimator 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJkyNoAperCorr3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Default extended source Y (2.0 arcsec aperture diameter, but no aperture correction applied) aperture calibrated flux If in doubt use this flux estimator 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJkyNoAperCorr4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Extended source Y (2.8 arcsec aperture diameter, but no aperture correction applied) aperture calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJkyNoAperCorr4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Extended source Y (2.8 arcsec aperture diameter, but no aperture correction applied) aperture calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJkyNoAperCorr6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Extended source Y (5.7 arcsec aperture diameter, but no aperture correction applied) aperture calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperJkyNoAperCorr6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Extended source Y (5.7 arcsec aperture diameter, but no aperture correction applied) aperture calibrated flux 
real 
4 
jansky 
0.9999995e9 
phot.flux 
yAperLup3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Default point source Y aperture corrected (2.0 arcsec aperture diameter) luptitude If in doubt use this flux estimator 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLup3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Default point source Y aperture corrected (2.0 arcsec aperture diameter) luptitude If in doubt use this flux estimator 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLup3Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in default point/extended source Y (2.0 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
stat.error 
yAperLup3Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in default point/extended source Y (2.0 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
stat.error 
yAperLup4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Point source Y aperture corrected (2.8 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLup4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Point source Y aperture corrected (2.8 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLup4Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in point/extended source Y (2.8 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
stat.error 
yAperLup4Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in point/extended source Y (2.8 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
stat.error 
yAperLup6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Point source Y aperture corrected (5.7 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLup6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Point source Y aperture corrected (5.7 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLup6Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in point/extended source Y (5.7 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
stat.error 
yAperLup6Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in point/extended source Y (5.7 arcsec aperture diameter) luptitude 
real 
4 
lup 
0.9999995e9 
stat.error 
yAperLupNoAperCorr3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Default extended source Y (2.0 arcsec aperture diameter, but no aperture correction applied) aperture luptitude If in doubt use this flux estimator 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLupNoAperCorr3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Default extended source Y (2.0 arcsec aperture diameter, but no aperture correction applied) aperture luptitude If in doubt use this flux estimator 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLupNoAperCorr4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Extended source Y (2.8 arcsec aperture diameter, but no aperture correction applied) aperture luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLupNoAperCorr4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Extended source Y (2.8 arcsec aperture diameter, but no aperture correction applied) aperture luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLupNoAperCorr6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Extended source Y (5.7 arcsec aperture diameter, but no aperture correction applied) aperture luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperLupNoAperCorr6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Extended source Y (5.7 arcsec aperture diameter, but no aperture correction applied) aperture luptitude 
real 
4 
lup 
0.9999995e9 
phot.lup 
yAperMag1 
vmcSynopticSource 
VMCDR1 
Extended source Y aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag1 
vmcSynopticSource 
VMCDR2 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCDR3 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCDR4 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20110816 
Extended source Y aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag1 
vmcSynopticSource 
VMCv20110909 
Extended source Y aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag1 
vmcSynopticSource 
VMCv20120126 
Extended source Y aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag1 
vmcSynopticSource 
VMCv20121128 
Extended source Y aperture corrected mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag1 
vmcSynopticSource 
VMCv20130304 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag1 
vmcSynopticSource 
VMCv20130805 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20140428 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20140903 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20150309 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20151218 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20160311 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20160822 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20170109 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20170411 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20171101 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20180702 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vmcSynopticSource 
VMCv20181120 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vvvSource 
VVVDR4 
Point source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1 
vvvSynopticSource 
VVVDR4 
Extended source Y aperture corrected mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Y mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag1Err 
vmcSynopticSource 
VMCDR4 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Y mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Y mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Y mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Y mag (0.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag1Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag1Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag1Err 
vmcSynopticSource 
VMCv20151218 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20160311 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20160822 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20170109 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20170411 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20171101 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20180702 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vmcSynopticSource 
VMCv20181120 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vvvSource 
VVVDR4 
Error in point source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag1Err 
vvvSynopticSource 
VVVDR4 
Error in extended source Y mag (1.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCDR1 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag2 
vmcSynopticSource 
VMCDR2 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCDR3 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCDR4 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20110816 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag2 
vmcSynopticSource 
VMCv20110909 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag2 
vmcSynopticSource 
VMCv20120126 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag2 
vmcSynopticSource 
VMCv20121128 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag2 
vmcSynopticSource 
VMCv20130304 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag2 
vmcSynopticSource 
VMCv20130805 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20140428 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20140903 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20150309 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20151218 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20160311 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20160822 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20170109 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20170411 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20171101 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20180702 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vmcSynopticSource 
VMCv20181120 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2 
vvvSynopticSource 
VVVDR4 
Extended source Y aperture corrected mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag2Err 
vmcSynopticSource 
VMCDR4 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag2Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag2Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag2Err 
vmcSynopticSource 
VMCv20151218 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20160311 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20160822 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20170109 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20170411 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20171101 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20180702 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vmcSynopticSource 
VMCv20181120 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag2Err 
vvvSynopticSource 
VVVDR4 
Error in extended source Y mag (1.4 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSDR1 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vhsSource 
VHSDR2 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vhsSource 
VHSDR3 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSDR4 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSDR6 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSv20120926 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vhsSource 
VHSv20130417 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vhsSource 
VHSv20140409 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSv20150108 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSv20160114 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSv20160507 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSv20170630 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vhsSource 
VHSv20180419 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
videoSource 
VIDEODR2 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
videoSource 
VIDEODR3 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
videoSource 
VIDEODR4 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
videoSource 
VIDEODR5 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
videoSource 
VIDEOv20100513 
Default point/extended source Y mag, no aperture correction applied If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
videoSource 
VIDEOv20111208 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingSource 
VIKINGDR2 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingSource 
VIKINGDR3 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingSource 
VIKINGDR4 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20110714 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingSource 
VIKINGv20111019 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingSource 
VIKINGv20130417 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingSource 
VIKINGv20140402 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20150421 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20151230 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20160406 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20161202 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20170715 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingSource 
VIKINGv20181012 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Default point source Y aperture corrected (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Default point source Y aperture corrected (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCDR1 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCDR2 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCDR3 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCDR4 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20110816 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCv20110909 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCv20120126 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCv20121128 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCv20130304 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSource 
VMCv20130805 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20140428 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20140903 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20150309 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20151218 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20160311 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20160822 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20170109 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20170411 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20171101 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20180702 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSource 
VMCv20181120 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCDR1 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSynopticSource 
VMCDR2 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCDR3 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCDR4 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20110816 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSynopticSource 
VMCv20110909 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSynopticSource 
VMCv20120126 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSynopticSource 
VMCv20121128 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSynopticSource 
VMCv20130304 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag3 
vmcSynopticSource 
VMCv20130805 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20140428 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20140903 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20150309 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20151218 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20160311 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20160822 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20170109 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20170411 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20171101 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20180702 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vmcSynopticSource 
VMCv20181120 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vvvSource 
VVVDR4 
Default point source Y aperture corrected mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3 
vvvSynopticSource 
VVVDR4 
Default point/extended source Y aperture corrected mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSDR1 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vhsSource 
VHSDR2 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vhsSource 
VHSDR3 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSDR4 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
vhsSource 
VHSDR6 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSv20120926 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vhsSource 
VHSv20130417 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vhsSource 
VHSv20140409 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSv20150108 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
vhsSource 
VHSv20160114 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSv20160507 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSv20170630 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vhsSource 
VHSv20180419 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
videoSource 
VIDEODR2 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
videoSource 
VIDEODR3 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
videoSource 
VIDEODR4 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
videoSource 
VIDEODR5 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
videoSource 
VIDEOv20100513 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
videoSource 
VIDEOv20111208 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGDR2 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGDR3 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGDR4 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag3Err 
vikingSource 
VIKINGv20110714 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGv20111019 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGv20130417 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGv20140402 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingSource 
VIKINGv20150421 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
vikingSource 
VIKINGv20151230 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vikingSource 
VIKINGv20160406 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vikingSource 
VIKINGv20161202 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vikingSource 
VIKINGv20170715 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vikingSource 
VIKINGv20181012 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in default point/extended source Y (2.0 arcsec aperture diameter) magnitude 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in default point/extended source Y (2.0 arcsec aperture diameter) magnitude 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCDR2 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCDR3 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
vmcSource 
VMCDR4 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20110816 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCv20110909 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCv20120126 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCv20121128 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCv20130304 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCv20130805 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vmcSource 
VMCv20140428 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20140903 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
vmcSource 
VMCv20150309 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag3Err 
vmcSource 
VMCv20151218 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20160311 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20160822 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20170109 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20170411 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20171101 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20180702 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource 
VMCv20181120 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vmcSource, vmcSynopticSource 
VMCDR1 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag3Err 
vvvSource 
VVVDR4 
Error in default point source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag3Err 
vvvSynopticSource 
VVVDR4 
Error in default point/extended source Y mag (2.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSDR1 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vhsSource 
VHSDR2 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vhsSource 
VHSDR3 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSDR4 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSDR6 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSv20120926 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vhsSource 
VHSv20130417 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vhsSource 
VHSv20140409 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSv20150108 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSv20160114 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSv20160507 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSv20170630 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vhsSource 
VHSv20180419 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
videoSource 
VIDEODR2 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
videoSource 
VIDEODR3 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
videoSource 
VIDEODR4 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
videoSource 
VIDEODR5 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
videoSource 
VIDEOv20100513 
Extended source Y mag, no aperture correction applied 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
videoSource 
VIDEOv20111208 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingSource 
VIKINGDR2 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingSource 
VIKINGDR3 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingSource 
VIKINGDR4 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20110714 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingSource 
VIKINGv20111019 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingSource 
VIKINGv20130417 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingSource 
VIKINGv20140402 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20150421 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20151230 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20160406 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20161202 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20170715 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingSource 
VIKINGv20181012 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Point source Y aperture corrected (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Point source Y aperture corrected (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCDR1 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCDR2 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCDR3 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCDR4 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20110816 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCv20110909 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCv20120126 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCv20121128 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCv20130304 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSource 
VMCv20130805 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20140428 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20140903 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20150309 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20151218 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20160311 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20160822 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20170109 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20170411 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20171101 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20180702 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSource 
VMCv20181120 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCDR1 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSynopticSource 
VMCDR2 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCDR3 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCDR4 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20110816 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSynopticSource 
VMCv20110909 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSynopticSource 
VMCv20120126 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSynopticSource 
VMCv20121128 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSynopticSource 
VMCv20130304 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag4 
vmcSynopticSource 
VMCv20130805 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20140428 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20140903 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20150309 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20151218 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20160311 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20160822 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20170109 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20170411 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20171101 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20180702 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vmcSynopticSource 
VMCv20181120 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vvvSource 
VVVDR4 
Point source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4 
vvvSynopticSource 
VVVDR4 
Extended source Y aperture corrected mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSDR1 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vhsSource 
VHSDR2 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vhsSource 
VHSDR3 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSDR4 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vhsSource 
VHSDR6 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSv20120926 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vhsSource 
VHSv20130417 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vhsSource 
VHSv20140409 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSv20150108 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vhsSource 
VHSv20160114 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSv20160507 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSv20170630 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vhsSource 
VHSv20180419 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
videoSource 
VIDEODR2 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
videoSource 
VIDEODR3 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
videoSource 
VIDEODR4 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
videoSource 
VIDEODR5 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
videoSource 
VIDEOv20100513 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
videoSource 
VIDEOv20111208 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGDR2 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGDR3 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGDR4 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag4Err 
vikingSource 
VIKINGv20110714 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGv20111019 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGv20130417 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGv20140402 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingSource 
VIKINGv20150421 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vikingSource 
VIKINGv20151230 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vikingSource 
VIKINGv20160406 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vikingSource 
VIKINGv20161202 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vikingSource 
VIKINGv20170715 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vikingSource 
VIKINGv20181012 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in point/extended source Y (2.8 arcsec aperture diameter) magnitude 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in point/extended source Y (2.8 arcsec aperture diameter) magnitude 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCDR1 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCDR2 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCDR3 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vmcSource 
VMCDR4 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20110816 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCv20110909 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCv20120126 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCv20121128 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCv20130304 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCv20130805 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSource 
VMCv20140428 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20140903 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vmcSource 
VMCv20150309 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vmcSource 
VMCv20151218 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20160311 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20160822 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20170109 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20170411 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20171101 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20180702 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSource 
VMCv20181120 
Error in point/extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vmcSynopticSource 
VMCDR4 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag4Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag4Err 
vmcSynopticSource 
VMCv20151218 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20160311 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20160822 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20170109 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20170411 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20171101 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20180702 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vmcSynopticSource 
VMCv20181120 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vvvSource 
VVVDR4 
Error in point source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag4Err 
vvvSynopticSource 
VVVDR4 
Error in extended source Y mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCDR1 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag5 
vmcSynopticSource 
VMCDR2 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCDR3 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCDR4 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20110816 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag5 
vmcSynopticSource 
VMCv20110909 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag5 
vmcSynopticSource 
VMCv20120126 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag5 
vmcSynopticSource 
VMCv20121128 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag5 
vmcSynopticSource 
VMCv20130304 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag5 
vmcSynopticSource 
VMCv20130805 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20140428 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20140903 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20150309 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20151218 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20160311 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20160822 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20170109 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20170411 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20171101 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20180702 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vmcSynopticSource 
VMCv20181120 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5 
vvvSynopticSource 
VVVDR4 
Extended source Y aperture corrected mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCDR1 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCDR2 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCDR3 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag5Err 
vmcSynopticSource 
VMCDR4 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20110816 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCv20110909 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCv20120126 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCv20121128 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCv20130304 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCv20130805 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag5Err 
vmcSynopticSource 
VMCv20140428 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20140903 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag5Err 
vmcSynopticSource 
VMCv20150309 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag5Err 
vmcSynopticSource 
VMCv20151218 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20160311 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20160822 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20170109 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20170411 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20171101 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20180702 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vmcSynopticSource 
VMCv20181120 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag5Err 
vvvSynopticSource 
VVVDR4 
Error in extended source Y mag (4.0 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSDR1 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vhsSource 
VHSDR2 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vhsSource 
VHSDR3 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSDR4 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSDR6 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSv20120926 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vhsSource 
VHSv20130417 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vhsSource 
VHSv20140409 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSv20150108 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSv20160114 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSv20160507 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSv20170630 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vhsSource 
VHSv20180419 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
videoSource 
VIDEODR2 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
videoSource 
VIDEODR3 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
videoSource 
VIDEODR4 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
videoSource 
VIDEODR5 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
videoSource 
VIDEOv20100513 
Extended source Y mag, no aperture correction applied 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
videoSource 
VIDEOv20111208 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingSource 
VIKINGDR2 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingSource 
VIKINGDR3 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingSource 
VIKINGDR4 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20110714 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingSource 
VIKINGv20111019 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingSource 
VIKINGv20130417 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingSource 
VIKINGv20140402 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20150421 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20151230 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20160406 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20161202 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20170715 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingSource 
VIKINGv20181012 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Point source Y aperture corrected (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Point source Y aperture corrected (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCDR1 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCDR2 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCDR3 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCDR4 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20110816 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCv20110909 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCv20120126 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCv20121128 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCv20130304 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMag6 
vmcSource 
VMCv20130805 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20140428 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20140903 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20150309 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20151218 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20160311 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20160822 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20170109 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20170411 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20171101 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20180702 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6 
vmcSource 
VMCv20181120 
Point source Y aperture corrected mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSDR1 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vhsSource 
VHSDR2 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vhsSource 
VHSDR3 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSDR4 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
vhsSource 
VHSDR6 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSv20120926 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vhsSource 
VHSv20130417 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vhsSource 
VHSv20140409 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSv20150108 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
vhsSource 
VHSv20160114 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSv20160507 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSv20170630 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vhsSource 
VHSv20180419 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
videoSource 
VIDEODR2 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
videoSource 
VIDEODR3 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
videoSource 
VIDEODR4 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
videoSource 
VIDEODR5 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
videoSource 
VIDEOv20100513 
Error in extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
videoSource 
VIDEOv20111208 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGDR2 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGDR3 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGDR4 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag6Err 
vikingSource 
VIKINGv20110714 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGv20111019 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGv20130417 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGv20140402 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingSource 
VIKINGv20150421 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
vikingSource 
VIKINGv20151230 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vikingSource 
VIKINGv20160406 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vikingSource 
VIKINGv20161202 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vikingSource 
VIKINGv20170715 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vikingSource 
VIKINGv20181012 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Error in point/extended source Y (5.7 arcsec aperture diameter) magnitude 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Error in point/extended source Y (5.7 arcsec aperture diameter) magnitude 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCDR1 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCDR2 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCDR3 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
vmcSource 
VMCDR4 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20110816 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCv20110909 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCv20120126 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCv20121128 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCv20130304 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCv20130805 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error 
yAperMag6Err 
vmcSource 
VMCv20140428 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20140903 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
vmcSource 
VMCv20150309 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yAperMag6Err 
vmcSource 
VMCv20151218 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20160311 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20160822 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20170109 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20170411 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20171101 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20180702 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMag6Err 
vmcSource 
VMCv20181120 
Error in point/extended source Y mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSDR1 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vhsSource 
VHSDR2 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vhsSource 
VHSDR3 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSDR4 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSDR6 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSv20120926 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vhsSource 
VHSv20130417 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vhsSource 
VHSv20140409 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSv20150108 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSv20160114 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSv20160507 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSv20170630 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vhsSource 
VHSv20180419 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
videoSource 
VIDEODR2 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
videoSource 
VIDEODR3 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
videoSource 
VIDEODR4 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
videoSource 
VIDEODR5 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
videoSource 
VIDEOv20111208 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingSource 
VIKINGDR2 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingSource 
VIKINGDR3 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingSource 
VIKINGDR4 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20110714 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20111019 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20130417 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20140402 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20150421 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20151230 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20160406 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20161202 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20170715 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingSource 
VIKINGv20181012 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Default extended source Y (2.0 arcsec aperture diameter, but no aperture correction applied) aperture magnitude If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Default extended source Y (2.0 arcsec aperture diameter, but no aperture correction applied) aperture magnitude If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCDR1 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCDR2 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCDR3 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCDR4 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20110816 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCv20110909 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCv20120126 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCv20121128 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCv20130304 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr3 
vmcSource 
VMCv20130805 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20140428 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20140903 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20150309 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20151218 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20160311 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20160822 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20170109 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20170411 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20171101 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20180702 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr3 
vmcSource 
VMCv20181120 
Default extended source Y aperture mag (2.0 arcsec aperture diameter) If in doubt use this flux estimator 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSDR1 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vhsSource 
VHSDR2 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vhsSource 
VHSDR3 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSDR4 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSDR6 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSv20120926 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vhsSource 
VHSv20130417 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vhsSource 
VHSv20140409 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSv20150108 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSv20160114 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSv20160507 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSv20170630 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vhsSource 
VHSv20180419 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
videoSource 
VIDEODR2 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
videoSource 
VIDEODR3 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
videoSource 
VIDEODR4 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
videoSource 
VIDEODR5 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
videoSource 
VIDEOv20111208 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingSource 
VIKINGDR2 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingSource 
VIKINGDR3 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingSource 
VIKINGDR4 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20110714 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20111019 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20130417 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20140402 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20150421 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20151230 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20160406 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20161202 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20170715 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingSource 
VIKINGv20181012 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Extended source Y (2.8 arcsec aperture diameter, but no aperture correction applied) aperture magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Extended source Y (2.8 arcsec aperture diameter, but no aperture correction applied) aperture magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCDR1 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCDR2 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCDR3 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCDR4 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20110816 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCv20110909 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCv20120126 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCv20121128 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCv20130304 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr4 
vmcSource 
VMCv20130805 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20140428 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20140903 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20150309 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20151218 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20160311 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20160822 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20170109 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20170411 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20171101 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20180702 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr4 
vmcSource 
VMCv20181120 
Extended source Y aperture mag (2.8 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSDR1 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vhsSource 
VHSDR2 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vhsSource 
VHSDR3 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSDR4 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSDR6 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSv20120926 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vhsSource 
VHSv20130417 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vhsSource 
VHSv20140409 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSv20150108 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSv20160114 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSv20160507 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSv20170630 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vhsSource 
VHSv20180419 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
videoSource 
VIDEODR2 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
videoSource 
VIDEODR3 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
videoSource 
VIDEODR4 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
videoSource 
VIDEODR5 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
videoSource 
VIDEOv20111208 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingSource 
VIKINGDR2 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingSource 
VIKINGDR3 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingSource 
VIKINGDR4 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20110714 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20111019 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20130417 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20140402 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20150421 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20151230 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20160406 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20161202 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20170715 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingSource 
VIKINGv20181012 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Extended source Y (5.7 arcsec aperture diameter, but no aperture correction applied) aperture magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Extended source Y (5.7 arcsec aperture diameter, but no aperture correction applied) aperture magnitude 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCDR1 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCDR2 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCDR3 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCDR4 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20110816 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCv20110909 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCv20120126 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCv20121128 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCv20130304 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yAperMagNoAperCorr6 
vmcSource 
VMCv20130805 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20140428 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20140903 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20150309 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20151218 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20160311 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20160822 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20170109 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20170411 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20171101 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20180702 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yAperMagNoAperCorr6 
vmcSource 
VMCv20181120 
Extended source Y aperture mag (5.7 arcsec aperture diameter) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yaStratAst 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
videoVarFrameSetInfo 
VIDEODR5 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCDR4 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20151218 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20160311 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20160822 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20170109 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20170411 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20171101 
Strateva parameter, a, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20180702 
Parameter, c0 from FerreiraLopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratAst 
vmcVarFrameSetInfo 
VMCv20181120 
Parameter, c0 from FerreiraLopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
yaStratPht 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
videoVarFrameSetInfo 
VIDEODR5 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCDR4 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20151218 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20160311 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20160822 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20170109 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20170411 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20171101 
Strateva parameter, a, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20180702 
Parameter, c0 from FerreiraLopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yaStratPht 
vmcVarFrameSetInfo 
VMCv20181120 
Parameter, c0 from FerreiraLopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yAverageConf 
vhsSource 
VHSDR1 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vhsSource 
VHSDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vhsSource 
VHSDR3 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSDR4 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSDR6 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20120926 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20130417 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20140409 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20150108 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20160114 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20160507 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20170630 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vhsSource 
VHSv20180419 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vikingSource 
VIKINGDR3 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGDR4 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20110714 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vikingSource 
VIKINGv20111019 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vikingSource 
VIKINGv20130417 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20140402 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20150421 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20151230 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20160406 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20161202 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20170715 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingSource 
VIKINGv20181012 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCDR2 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCDR3 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCDR4 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20110816 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vmcSource 
VMCv20110909 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vmcSource 
VMCv20120126 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vmcSource 
VMCv20121128 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20130304 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20130805 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20140428 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20140903 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20150309 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20151218 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20160311 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20160822 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20170109 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20170411 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20171101 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20180702 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource 
VMCv20181120 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
yAverageConf 
vmcSource, vmcSynopticSource 
VMCDR1 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

99999999 
meta.code 
yAverageConf 
vvvSource, vvvSynopticSource 
VVVDR4 
average confidence in 2 arcsec diameter default aperture (aper3) Y 
real 
4 

0.9999995e9 
stat.likelihood;em.IR.NIR 
YB 
eros2LMCSource, eros2SMCSource, erosLMCSource, erosSMCSource 
EROS 
Y pixel coordinate on blue reference images relative to rebined reference images in [klmn] frame 
real 
4 



ybestAper 
videoVariability 
VIDEODR2 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
videoVariability 
VIDEODR3 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
videoVariability 
VIDEODR4 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
videoVariability 
VIDEODR5 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
videoVariability 
VIDEOv20100513 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
videoVariability 
VIDEOv20111208 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vikingVariability 
VIKINGv20110714 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCDR1 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCDR2 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCDR3 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCDR4 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20110816 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20110909 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20120126 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 

Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20121128 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20130304 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20130805 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20140428 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20140903 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20150309 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20151218 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20160311 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20160822 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20170109 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20170411 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20171101 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20180702 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybestAper 
vmcVariability 
VMCv20181120 
Best aperture (16) for photometric statistics in the Y band 
int 
4 

9999 
meta.code.class;em.IR.NIR 
Aperture magnitude (16) which gives the lowest RMS for the object. All apertures have the appropriate aperture correction. This can give better values in crowded regions than aperMag3 (see Irwin et al. 2007, MNRAS, 375, 1449) 
ybStratAst 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
videoVarFrameSetInfo 
VIDEODR5 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCDR4 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20151218 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20160311 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20160822 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20170109 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20170411 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20171101 
Strateva parameter, b, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20180702 
Parameter, c1 from FerreiraLopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratAst 
vmcVarFrameSetInfo 
VMCv20181120 
Parameter, c1 from FerreiraLopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ybStratPht 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
videoVarFrameSetInfo 
VIDEODR5 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCDR4 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20151218 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20160311 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20160822 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20170109 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20170411 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20171101 
Strateva parameter, b, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20180702 
Parameter, c1 from FerreiraLopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ybStratPht 
vmcVarFrameSetInfo 
VMCv20181120 
Parameter, c1 from FerreiraLopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqAst 
videoVarFrameSetInfo 
VIDEODR2 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
videoVarFrameSetInfo 
VIDEODR3 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
videoVarFrameSetInfo 
VIDEODR4 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
videoVarFrameSetInfo 
VIDEODR5 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCDR1 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCDR2 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCDR3 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCDR4 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20110816 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20110909 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20120126 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20121128 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20130304 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20130805 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20140428 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20140903 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20150309 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20151218 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20160311 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20160822 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20170109 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20170411 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20171101 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20180702 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqAst 
vmcVarFrameSetInfo 
VMCv20181120 
Goodness of fit of Strateva function to astrometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ychiSqpd 
videoVariability 
VIDEODR2 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
videoVariability 
VIDEODR3 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
videoVariability 
VIDEODR4 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
videoVariability 
VIDEODR5 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
videoVariability 
VIDEOv20100513 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
videoVariability 
VIDEOv20111208 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vikingVariability 
VIKINGv20110714 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCDR1 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCDR2 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCDR3 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCDR4 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20110816 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20110909 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20120126 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20121128 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20130304 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20130805 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20140428 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20140903 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20150309 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20151218 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20160311 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20160822 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20170109 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20170411 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20171101 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20180702 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqpd 
vmcVariability 
VMCv20181120 
Chi square (per degree of freedom) fit to data (mean and expected rms) 
real 
4 

0.9999995e9 
stat.fit.chi2;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
ychiSqPht 
videoVarFrameSetInfo 
VIDEODR2 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
videoVarFrameSetInfo 
VIDEODR3 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
videoVarFrameSetInfo 
VIDEODR4 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
videoVarFrameSetInfo 
VIDEODR5 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCDR1 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCDR2 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCDR3 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCDR4 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20110816 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20110909 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20120126 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20121128 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20130304 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20130805 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20140428 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20140903 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20150309 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20151218 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20160311 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20160822 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20170109 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20170411 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20171101 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20180702 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ychiSqPht 
vmcVarFrameSetInfo 
VMCv20181120 
Goodness of fit of Strateva function to photometric data in Y band 
real 
4 

0.9999995e9 
stat.fit.goodness;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
Yclass 
vvvParallaxCatalogue, vvvProperMotionCatalogue 
VVVDR4 
VVV DR4 Y morphological classification. 1 = galaxy,0 = noise,1 = stellar,2 = probably stellar,3 = probable galaxy,7 = bad pixel within 2" aperture,9 = saturated {catalogue TType keyword: Yclass} 
int 
4 

99999999 

yClass 
vhsSource 
VHSDR2 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vhsSource 
VHSDR3 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSDR4 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSDR6 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSv20120926 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vhsSource 
VHSv20130417 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vhsSource 
VHSv20140409 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSv20150108 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSv20160114 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSv20160507 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSv20170630 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource 
VHSv20180419 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
videoSource 
VIDEODR2 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
videoSource 
VIDEODR3 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
videoSource 
VIDEODR4 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
videoSource 
VIDEODR5 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
videoSource 
VIDEOv20111208 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingSource 
VIKINGDR2 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingSource 
VIKINGDR3 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingSource 
VIKINGDR4 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource 
VIKINGv20111019 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingSource 
VIKINGv20130417 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingSource 
VIKINGv20140402 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingSource 
VIKINGv20150421 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource 
VIKINGv20151230 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource 
VIKINGv20160406 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource 
VIKINGv20161202 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource 
VIKINGv20170715 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource 
VIKINGv20181012 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCDR2 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCDR3 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCDR4 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20110909 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCv20120126 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCv20121128 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCv20130304 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCv20130805 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource 
VMCv20140428 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20140903 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20150309 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20151218 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20160311 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20160822 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20170109 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20170411 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20171101 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20180702 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource 
VMCv20181120 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClass 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vmcSource, vmcSynopticSource 
VMCDR1 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class 
yClass 
vvvSource, vvvSynopticSource 
VVVDR4 
discrete image classification flag in Y 
smallint 
2 

9999 
src.class;em.IR.NIR 
yClassStat 
vhsSource 
VHSDR2 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vhsSource 
VHSDR3 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSDR4 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSDR6 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSv20120926 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vhsSource 
VHSv20130417 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vhsSource 
VHSv20140409 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSv20150108 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSv20160114 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSv20160507 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSv20170630 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource 
VHSv20180419 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
videoSource 
VIDEODR2 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
videoSource 
VIDEODR3 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
videoSource 
VIDEODR4 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
videoSource 
VIDEODR5 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
videoSource 
VIDEOv20100513 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
videoSource 
VIDEOv20111208 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
videoSourceRemeasurement 
VIDEOv20100513 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingSource 
VIKINGDR2 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingSource 
VIKINGDR3 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingSource 
VIKINGDR4 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource 
VIKINGv20111019 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingSource 
VIKINGv20130417 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingSource 
VIKINGv20140402 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingSource 
VIKINGv20150421 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource 
VIKINGv20151230 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource 
VIKINGv20160406 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource 
VIKINGv20161202 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource 
VIKINGv20170715 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource 
VIKINGv20181012 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCDR2 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCDR3 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCDR4 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20110909 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCv20120126 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCv20121128 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCv20130304 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCv20130805 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource 
VMCv20140428 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20140903 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20150309 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20151218 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20160311 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20160822 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20170109 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20170411 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20171101 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20180702 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource 
VMCv20181120 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vmcSource, vmcSynopticSource 
VMCDR1 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat 
yClassStat 
vvvSource 
VVVDR4 
SExtractor classification statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
yClassStat 
vvvSynopticSource 
VVVDR4 
N(0,1) stellarnessofprofile statistic in Y 
real 
4 

0.9999995e9 
stat;em.IR.NIR 
ycStratAst 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
videoVarFrameSetInfo 
VIDEODR5 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCDR4 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20151218 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20160311 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20160822 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20170109 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20170411 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20171101 
Strateva parameter, c, in fit to astrometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20180702 
Parameter, c2 from FerreiraLopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratAst 
vmcVarFrameSetInfo 
VMCv20181120 
Parameter, c2 from FerreiraLopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS position around the mean for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. 
ycStratPht 
videoVarFrameSetInfo 
VIDEODR2 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
videoVarFrameSetInfo 
VIDEODR3 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
videoVarFrameSetInfo 
VIDEODR4 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
videoVarFrameSetInfo 
VIDEODR5 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
videoVarFrameSetInfo 
VIDEOv20100513 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vikingVarFrameSetInfo 
VIKINGv20110714 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCDR1 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCDR2 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCDR3 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCDR4 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20110816 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20110909 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20120126 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 

The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20121128 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20130304 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20130805 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20140428 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20140903 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20150309 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20151218 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20160311 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20160822 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20170109 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20170411 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20171101 
Strateva parameter, c, in fit to photometric rms vs magnitude in Y band, see Sesar et al. 2007. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20180702 
Parameter, c2 from FerreiraLopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
ycStratPht 
vmcVarFrameSetInfo 
VMCv20181120 
Parameter, c2 from FerreiraLopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Y band. 
real 
4 

0.9999995e9 
stat.fit.param;em.IR.NIR 
The best fit solution to the expected RMS brightness (in magnitudes) for all objects in the frameset. Objects were binned in ranges of magnitude and the median RMS (after clipping out variable objects using the medianabsolute deviation) was calculated. The Strateva function $\zeta(m)>=a+b\,10^{0.4m}+c\,10^{0.8m}$ was fit, where $\zeta(m)$ is the expected RMS as a function of magnitude. The chisquared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236. 
yDeblend 
vhsSourceRemeasurement 
VHSDR1 
placeholder flag indicating parent/child relation in Y 
int 
4 

99999999 
meta.code 
yDeblend 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
placeholder flag indicating parent/child relation in Y 
int 
4 

99999999 
meta.code 
yDeblend 
vikingSourceRemeasurement 
VIKINGv20110714 
placeholder flag indicating parent/child relation in Y 
int 
4 

99999999 
meta.code 
yDeblend 
vikingSourceRemeasurement 
VIKINGv20111019 
placeholder flag indicating parent/child relation in Y 
int 
4 

99999999 
meta.code 
yDeblend 
vmcSourceRemeasurement 
VMCv20110816 
placeholder flag indicating parent/child relation in Y 
int 
4 

99999999 
meta.code 
yDeblend 
vmcSourceRemeasurement 
VMCv20110909 
placeholder flag indicating parent/child relation in Y 
int 
4 

99999999 
meta.code 
Yell 
vvvParallaxCatalogue, vvvProperMotionCatalogue 
VVVDR4 
Ellipticity of the DR4 Y detection. {catalogue TType keyword: Yell} 
real 
4 

999999500.0 

yEll 
vhsSource 
VHSDR2 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vhsSource 
VHSDR3 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSDR4 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSDR6 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSv20120926 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vhsSource 
VHSv20130417 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vhsSource 
VHSv20140409 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSv20150108 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSv20160114 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSv20160507 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSv20170630 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource 
VHSv20180419 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
videoSource 
VIDEODR2 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
videoSource 
VIDEODR3 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
videoSource 
VIDEODR4 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
videoSource 
VIDEODR5 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
videoSource 
VIDEOv20111208 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingSource 
VIKINGDR2 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingSource 
VIKINGDR3 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingSource 
VIKINGDR4 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource 
VIKINGv20111019 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingSource 
VIKINGv20130417 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingSource 
VIKINGv20140402 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingSource 
VIKINGv20150421 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource 
VIKINGv20151230 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource 
VIKINGv20160406 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource 
VIKINGv20161202 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource 
VIKINGv20170715 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource 
VIKINGv20181012 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCDR2 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCDR3 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCDR4 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20110909 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCv20120126 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCv20121128 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCv20130304 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCv20130805 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource 
VMCv20140428 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20140903 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20150309 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20151218 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20160311 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20160822 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20170109 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20170411 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20171101 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20180702 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource 
VMCv20181120 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yEll 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vmcSource, vmcSynopticSource 
VMCDR1 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity 
yEll 
vvvSource, vvvSynopticSource 
VVVDR4 
1b/a, where a/b=semimajor/minor axes in Y 
real 
4 

0.9999995e9 
src.ellipticity;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSDR1 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vhsMergeLog 
VHSDR2 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vhsMergeLog 
VHSDR3 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSDR4 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSDR6 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSv20120926 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vhsMergeLog 
VHSv20130417 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vhsMergeLog 
VHSv20140409 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSv20150108 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSv20160114 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSv20160507 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSv20170630 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vhsMergeLog 
VHSv20180419 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
videoMergeLog 
VIDEODR2 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
videoMergeLog 
VIDEODR3 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
videoMergeLog 
VIDEODR4 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
videoMergeLog 
VIDEODR5 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
videoMergeLog 
VIDEOv20100513 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
videoMergeLog 
VIDEOv20111208 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGDR2 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGDR3 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGDR4 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingMergeLog 
VIKINGv20110714 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGv20111019 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGv20130417 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGv20140402 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingMergeLog 
VIKINGv20150421 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingMergeLog 
VIKINGv20151230 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingMergeLog 
VIKINGv20160406 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingMergeLog 
VIKINGv20161202 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingMergeLog 
VIKINGv20170715 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingMergeLog 
VIKINGv20181012 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vikingZY_selJ_RemeasMergeLog 
VIKINGZYSELJv20160909 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vikingZY_selJ_RemeasMergeLog 
VIKINGZYSELJv20170124 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCDR2 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCDR3 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCDR4 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20110816 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCv20110909 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCv20120126 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCv20121128 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCv20130304 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCv20130805 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vmcMergeLog 
VMCv20140428 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20140903 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20150309 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20151218 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20160311 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20160822 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20170109 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20170411 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20171101 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20180702 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog 
VMCv20181120 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yeNum 
vmcMergeLog, vmcSynopticMergeLog 
VMCDR1 
the extension number of this Y frame 
tinyint 
1 


meta.number 
yeNum 
vvvMergeLog, vvvSynopticMergeLog 
VVVDR4 
the extension number of this Y frame 
tinyint 
1 


meta.number;em.IR.NIR 
yErr 
vhsDetection 
VHSDR2 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSDR3 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSDR4 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSDR6 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20120926 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20130417 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20140409 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20150108 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20160114 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20160507 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20170630 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection 
VHSv20180419 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vhsDetection, vhsListRemeasurement 
VHSDR1 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoDetection 
VIDEODR2 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoDetection 
VIDEODR3 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoDetection 
VIDEODR4 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoDetection 
VIDEODR5 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoDetection 
VIDEOv20100513 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoDetection 
VIDEOv20111208 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
videoListRemeasurement 
VIDEOv20100513 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGDR2 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGDR3 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGDR4 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20111019 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20130417 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20140402 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20150421 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20151230 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20160406 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20161202 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20170715 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection 
VIKINGv20181012 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingDetection, vikingListRemeasurement 
VIKINGv20110714 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingMapRemeasurement 
VIKINGZYSELJv20160909 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vikingMapRemeasurement 
VIKINGZYSELJv20170124 
Error in Y coordinate (SE: ERRY2_IMAGE^{½}) {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCDR1 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCDR2 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCDR3 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCDR4 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20110909 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20120126 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20121128 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20130304 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20130805 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20140428 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20140903 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20150309 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20151218 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20160311 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20160822 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20170109 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20170411 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20171101 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20180702 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection 
VMCv20181120 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vmcDetection, vmcListRemeasurement 
VMCv20110816 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
yErr 
vvvDetection 
VVVDR4 
Error in Y coordinate {catalogue TType keyword: Y_coordinate_err} Estimate of centroid error. 
real 
4 
pixels 

stat.error 
YERR_R 
spectra 
SIXDF 
error on Y_R position 
int 
4 



YERR_V 
spectra 
SIXDF 
error on Y_V position 
int 
4 



yErrBits 
vhsSource 
VHSDR1 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSDR2 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSDR3 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSDR4 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSDR6 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20120926 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20130417 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20140409 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20150108 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20160114 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20160507 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20170630 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSource 
VHSv20180419 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vhsSourceRemeasurement 
VHSDR1 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
yErrBits 
videoSource 
VIDEODR2 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

yErrBits 
videoSource 
VIDEODR3 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

yErrBits 
videoSource 
VIDEODR4 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

yErrBits 
videoSource 
VIDEODR5 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

yErrBits 
videoSource 
VIDEOv20100513 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

yErrBits 
videoSource 
VIDEOv20111208 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
This uses the FLAGS attribute in SE. The individual bit flags that this can be decomposed into are as follows: Bit Flag  Meaning   1  The object has neighbours, bright enough and close enough to significantly bias the MAG_AUTO photometry or bad pixels (more than 10% of photometry affected).   2  The object was originally blended with another   4  At least one pixel is saturated (or very close to)   8  The object is truncated (too close to an image boundary)   16  Object's aperture data are incomplete or corrupted   32  Object's isophotal data are imcomplete or corrupted. This is an old flag inherited from SE v1.0, and is kept for compatability reasons. It doesn't have any consequence for the extracted parameters.   64  Memory overflow occurred during deblending   128  Memory overflow occurred during extraction  

yErrBits 
videoSourceRemeasurement 
VIDEOv20100513 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
yErrBits 
vikingSource 
VIKINGDR2 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGDR3 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGDR4 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20110714 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20111019 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20130417 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20140402 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20150421 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20151230 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20160406 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20161202 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20170715 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSource 
VIKINGv20181012 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingSourceRemeasurement 
VIKINGv20110714 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
yErrBits 
vikingSourceRemeasurement 
VIKINGv20111019 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
yErrBits 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCDR2 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCDR3 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCDR4 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20110816 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20110909 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20120126 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20121128 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20130304 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20130805 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20140428 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20140903 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20150309 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20151218 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20160311 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20160822 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20170109 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20170411 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20171101 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20180702 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource 
VMCv20181120 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSource, vmcSynopticSource 
VMCDR1 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yErrBits 
vmcSourceRemeasurement 
VMCv20110816 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
yErrBits 
vmcSourceRemeasurement 
VMCv20110909 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code 
yErrBits 
vvvSource, vvvSynopticSource 
VVVDR4 
processing warning/error bitwise flags in Y 
int 
4 

99999999 
meta.code;em.IR.NIR 
Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture. 
yEta 
vhsSource 
VHSDR1 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSDR2 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSDR3 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSDR4 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSDR6 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20120926 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20130417 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20140409 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20150108 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20160114 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20160507 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20170630 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vhsSource 
VHSv20180419 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
videoSource 
VIDEODR2 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
videoSource 
VIDEODR3 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
videoSource 
VIDEODR4 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
videoSource 
VIDEODR5 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
videoSource 
VIDEOv20100513 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
videoSource 
VIDEOv20111208 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGDR2 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGDR3 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGDR4 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20110714 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20111019 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20130417 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20140402 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20150421 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20151230 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20160406 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20161202 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20170715 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vikingSource 
VIKINGv20181012 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCDR2 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCDR3 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCDR4 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20110816 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20110909 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20120126 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20121128 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20130304 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20130805 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20140428 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20140903 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20150309 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20151218 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20160311 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20160822 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20170109 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20170411 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20171101 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20180702 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource 
VMCv20181120 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vmcSource, vmcSynopticSource 
VMCDR1 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yEta 
vvvSource, vvvSynopticSource 
VVVDR4 
Offset of Y detection from master position (+north/south) 
real 
4 
arcsec 
0.9999995e9 
pos.eq.dec;arith.diff;em.IR.NIR 
When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 1.0 arcseconds is used. Such a large association criterion can of course lead to spurious pairings in the merged sources lists (although note that between passband pairs, handshake pairing is done: both passbands must agree that the candidate pair is their nearest neighbour for the pair to propagate through into the merged source table). In order to help filter spurious pairings out, and assuming that large positional offsets between the different passband detections are not expected (e.g. because of source motion, or larger than usual positional uncertainties) then the attributes Xi and Eta can be used to filter any pairings with suspiciously large offsets in one or more bands. For example, for a clean sample of QSOs from the VHS, you might wish to insist that the offsets in the selected sample are all below 0.5 arcsecond: simply add WHERE clauses into the SQL sample selection script to exclude all Xi and Eta values larger than the threshold you want. NB: the master position is the position of the detection in the shortest passband in the set, rather than the ra/dec of the source as stored in source attributes of the same name. The former is used in the pairing process, while the latter is generally the optimally weighted mean position from an astrometric solution or other combinatorial process of all individual detection positions across the available passbands. 
yexpML 
videoVarFrameSetInfo 
VIDEODR2 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
videoVarFrameSetInfo 
VIDEODR3 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
yexpML 
videoVarFrameSetInfo 
VIDEODR4 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
videoVarFrameSetInfo 
VIDEODR5 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
videoVarFrameSetInfo 
VIDEOv20100513 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
videoVarFrameSetInfo 
VIDEOv20111208 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
vikingVarFrameSetInfo 
VIKINGv20110714 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
vmcVarFrameSetInfo 
VMCDR1 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
vmcVarFrameSetInfo 
VMCDR2 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max;em.IR.NIR 
yexpML 
vmcVarFrameSetInfo 
VMCDR3 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCDR4 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20110816 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
vmcVarFrameSetInfo 
VMCv20110909 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
vmcVarFrameSetInfo 
VMCv20120126 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 

0.9999995e9 

yexpML 
vmcVarFrameSetInfo 
VMCv20121128 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
yexpML 
vmcVarFrameSetInfo 
VMCv20130304 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;stat.max;em.IR.NIR 
yexpML 
vmcVarFrameSetInfo 
VMCv20130805 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max;em.IR.NIR 
yexpML 
vmcVarFrameSetInfo 
VMCv20140428 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20140903 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20150309 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20151218 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20160311 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20160822 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20170109 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20170411 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20171101 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20180702 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yexpML 
vmcVarFrameSetInfo 
VMCv20181120 
Expected magnitude limit of frameSet in this in Y band. 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR;stat.max 
yExpRms 
videoVariability 
VIDEODR2 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
videoVariability 
VIDEODR3 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
videoVariability 
VIDEODR4 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
videoVariability 
VIDEODR5 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
videoVariability 
VIDEOv20100513 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
videoVariability 
VIDEOv20111208 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vikingVariability 
VIKINGv20110714 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCDR1 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCDR2 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCDR3 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCDR4 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20110816 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20110909 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20120126 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20121128 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20130304 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20130805 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20140428 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20140903 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20150309 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20151218 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20160311 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20160822 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20170109 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20170411 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20171101 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20180702 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yExpRms 
vmcVariability 
VMCv20181120 
Rms calculated from polynomial fit to modal RMS as a function of magnitude in Y band 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yGausig 
vhsSource 
VHSDR2 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vhsSource 
VHSDR3 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSDR4 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSDR6 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSv20120926 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vhsSource 
VHSv20130417 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vhsSource 
VHSv20140409 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSv20150108 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSv20160114 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSv20160507 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSv20170630 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource 
VHSv20180419 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vhsSource, vhsSourceRemeasurement 
VHSDR1 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
videoSource 
VIDEODR2 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
videoSource 
VIDEODR3 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
videoSource 
VIDEODR4 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
videoSource 
VIDEODR5 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
videoSource 
VIDEOv20111208 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
videoSource, videoSourceRemeasurement 
VIDEOv20100513 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingSource 
VIKINGDR2 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingSource 
VIKINGDR3 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingSource 
VIKINGDR4 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource 
VIKINGv20111019 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingSource 
VIKINGv20130417 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingSource 
VIKINGv20140402 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingSource 
VIKINGv20150421 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource 
VIKINGv20151230 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource 
VIKINGv20160406 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource 
VIKINGv20161202 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource 
VIKINGv20170715 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource 
VIKINGv20181012 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vikingSource, vikingSourceRemeasurement 
VIKINGv20110714 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCDR2 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCDR3 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCDR4 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20110909 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCv20120126 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCv20121128 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCv20130304 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCv20130805 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource 
VMCv20140428 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20140903 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20150309 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20151218 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20160311 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20160822 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20170109 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20170411 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20171101 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20180702 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource 
VMCv20181120 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yGausig 
vmcSource, vmcSourceRemeasurement 
VMCv20110816 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vmcSource, vmcSynopticSource 
VMCDR1 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param 
yGausig 
vvvSource, vvvSynopticSource 
VVVDR4 
RMS of axes of ellipse fit in Y 
real 
4 
pixels 
0.9999995e9 
src.morph.param;em.IR.NIR 
yHalfRad 
videoSource 
VIDEODR4 
SExtractor halflight radius in Y band 
real 
4 
pixels 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHalfRad 
videoSource 
VIDEODR5 
SExtractor halflight radius in Y band 
real 
4 
pixels 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSDR1 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
vhsSource 
VHSDR2 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
vhsSource 
VHSDR3 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSDR4 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSDR6 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSv20120926 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
yHlCorSMjRadAs 
vhsSource 
VHSv20130417 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
yHlCorSMjRadAs 
vhsSource 
VHSv20140409 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSv20150108 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSv20160114 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSv20160507 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSv20170630 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vhsSource 
VHSv20180419 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
videoSource 
VIDEODR2 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
videoSource 
VIDEODR3 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
yHlCorSMjRadAs 
videoSource 
VIDEODR4 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
videoSource 
VIDEODR5 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
videoSource 
VIDEOv20100513 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
videoSource 
VIDEOv20111208 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
vikingSource 
VIKINGDR2 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
vikingSource 
VIKINGDR3 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
yHlCorSMjRadAs 
vikingSource 
VIKINGDR4 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20110714 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20111019 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;src 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20130417 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20140402 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20150421 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20151230 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20160406 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20161202 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20170715 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yHlCorSMjRadAs 
vikingSource 
VIKINGv20181012 
Seeing corrected halflight, semimajor axis in Y band 
real 
4 
arcsec 
0.9999995e9 
phys.angSize;em.IR.NIR 
yIntRms 
videoVariability 
VIDEODR2 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
videoVariability 
VIDEODR3 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
videoVariability 
VIDEODR4 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
videoVariability 
VIDEODR5 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
videoVariability 
VIDEOv20100513 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
videoVariability 
VIDEOv20111208 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vikingVariability 
VIKINGv20110714 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCDR1 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCDR2 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCDR3 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCDR4 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20110816 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20110909 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20120126 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20121128 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20130304 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20130805 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20140428 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20140903 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20150309 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20151218 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20160311 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20160822 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20170109 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20170411 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20171101 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20180702 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yIntRms 
vmcVariability 
VMCv20181120 
Intrinsic rms in Yband 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yisDefAst 
videoVarFrameSetInfo 
VIDEODR2 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 

yisDefAst 
videoVarFrameSetInfo 
VIDEODR3 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
videoVarFrameSetInfo 
VIDEODR4 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
videoVarFrameSetInfo 
VIDEODR5 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
videoVarFrameSetInfo 
VIDEOv20111208 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 

yisDefAst 
vmcVarFrameSetInfo 
VMCDR1 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 

yisDefAst 
vmcVarFrameSetInfo 
VMCDR2 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCDR3 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCDR4 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20110816 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 

yisDefAst 
vmcVarFrameSetInfo 
VMCv20110909 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 

yisDefAst 
vmcVarFrameSetInfo 
VMCv20120126 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 

yisDefAst 
vmcVarFrameSetInfo 
VMCv20121128 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20130304 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20130805 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20140428 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20140903 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20150309 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20151218 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20160311 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20160822 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20170109 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20170411 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20171101 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20180702 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefAst 
vmcVarFrameSetInfo 
VMCv20181120 
Use a default model for the astrometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
videoVarFrameSetInfo 
VIDEODR2 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 

yisDefPht 
videoVarFrameSetInfo 
VIDEODR3 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
videoVarFrameSetInfo 
VIDEODR4 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
videoVarFrameSetInfo 
VIDEODR5 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
videoVarFrameSetInfo 
VIDEOv20111208 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 

yisDefPht 
vmcVarFrameSetInfo 
VMCDR1 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 

yisDefPht 
vmcVarFrameSetInfo 
VMCDR2 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCDR3 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCDR4 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20110816 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 

yisDefPht 
vmcVarFrameSetInfo 
VMCv20110909 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 

yisDefPht 
vmcVarFrameSetInfo 
VMCv20120126 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 

yisDefPht 
vmcVarFrameSetInfo 
VMCv20121128 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20130304 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20130805 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20140428 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20140903 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20150309 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20151218 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20160311 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20160822 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20170109 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20170411 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20171101 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20180702 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yisDefPht 
vmcVarFrameSetInfo 
VMCv20181120 
Use a default model for the photometric noise in Y band. 
tinyint 
1 

0 
meta.code;em.IR.NIR 
yIsMeas 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20160909 
Is pass band Y measured? 0 no, 1 yes 
tinyint 
1 

0 
meta.code 
yIsMeas 
vikingZY_selJ_SourceRemeasurement 
VIKINGZYSELJv20170124 
Is pass band Y measured? 0 no, 1 yes 
tinyint 
1 

0 
meta.code 
yjiWS 
vmcVariability 
VMCDR1 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 

The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCDR2 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCDR3 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.J;em.IR.K 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCDR4 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20110816 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 

The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20110909 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 

The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20120126 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 

The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20121128 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20130304 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20130805 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20140428 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.J;em.IR.K 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20140903 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.J;em.IR.K 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20150309 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.J;em.IR.K 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20151218 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20160311 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20160822 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20170109 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20170411 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20171101 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20180702 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yjiWS 
vmcVariability 
VMCv20181120 
WelchStetson statistic between Y and J. This assumes colour does not vary much and helps remove variation due to a few poor detections 
real 
4 

0.9999995e9 
stat.param;em.IR.NIR;em.IR.J 
The WelchStetson statistic is a measure of the correlation of the variability between two bands. We use the calculation in Welch D.L. and Stetson P.B. 1993, AJ, 105, 5, which is also used in Sesar et al. 2007, AJ, 134, 2236. We use the aperMag3 magnitude when comparing between bands. 
yKronMag 
videoSource 
VIDEODR4 
Extended source Y mag (Kron  SExtractor MAG_AUTO) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yKronMag 
videoSource 
VIDEODR5 
Extended source Y mag (Kron  SExtractor MAG_AUTO) 
real 
4 
mag 
0.9999995e9 
phot.mag;em.IR.NIR 
yKronMagErr 
videoSource 
VIDEODR4 
Extended source Y mag error (Kron  SExtractor MAG_AUTO) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
yKronMagErr 
videoSource 
VIDEODR5 
Extended source Y mag error (Kron  SExtractor MAG_AUTO) 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR;phot.mag 
Ymag 
vvvParallaxCatalogue, vvvProperMotionCatalogue 
VVVDR4 
VVV DR4 Y photometry {catalogue TType keyword: Ymag} 
real 
4 
mag 
999999500.0 

yMag 
vhsSourceRemeasurement 
VHSDR1 
Y mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yMag 
videoSourceRemeasurement 
VIDEOv20100513 
Y mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yMag 
vikingSourceRemeasurement 
VIKINGv20110714 
Y mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yMag 
vikingSourceRemeasurement 
VIKINGv20111019 
Y mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yMag 
vmcSourceRemeasurement 
VMCv20110816 
Y mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yMag 
vmcSourceRemeasurement 
VMCv20110909 
Y mag (as appropriate for this merged source) 
real 
4 
mag 
0.9999995e9 
phot.mag 
yMagErr 
vhsSourceRemeasurement 
VHSDR1 
Error in Y mag 
real 
4 
mag 
0.9999995e9 
stat.error 
yMagErr 
videoSourceRemeasurement 
VIDEOv20100513 
Error in Y mag 
real 
4 
mag 
0.9999995e9 
stat.error 
yMagErr 
vikingSourceRemeasurement 
VIKINGv20110714 
Error in Y mag 
real 
4 
mag 
0.9999995e9 
stat.error 
yMagErr 
vikingSourceRemeasurement 
VIKINGv20111019 
Error in Y mag 
real 
4 
mag 
0.9999995e9 
stat.error 
yMagErr 
vmcCepheidVariables 
VMCDR4 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20160311 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20160822 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20170109 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20170411 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20171101 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20180702 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcCepheidVariables 
VMCv20181120 
Error in intensityaveraged Y band magnitude {catalogue TType keyword: e_Ymag} 
real 
4 
mag 
0.9999995e9 
stat.error;phot.mag;em.IR.NIR 
yMagErr 
vmcSourceRemeasurement 
VMCv20110816 
Error in Y mag 
real 
4 
mag 
0.9999995e9 
stat.error 
yMagErr 
vmcSourceRemeasurement 
VMCv20110909 
Error in Y mag 
real 
4 
mag 
0.9999995e9 
stat.error 
yMagMAD 
videoVariability 
VIDEODR2 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
videoVariability 
VIDEODR3 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
videoVariability 
VIDEODR4 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
videoVariability 
VIDEODR5 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
videoVariability 
VIDEOv20100513 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
videoVariability 
VIDEOv20111208 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vikingVariability 
VIKINGv20110714 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCDR1 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCDR2 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCDR3 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCDR4 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20110816 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20110909 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20120126 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 

The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20121128 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20130304 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20130805 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.error;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20140428 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20140903 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 
VMCv20150309 
Median Absolute Deviation of Y magnitude 
real 
4 
mag 
0.9999995e9 
stat.err;em.IR.NIR;phot.mag 
The photometry is calculated for good observations in the best aperture. The mean, rms, median, median absolute deviation, minMag and maxMag are quite standard. The skewness is calculated as in Sesar et al. 2007, AJ, 134, 2236. The number of good detections that are more than 3 standard deviations can indicate a distribution with many outliers. In each frameset, the mean and rms are used to derive a fit to the expected rms as a function of magnitude. The parameters for the fit are stored in VarFrameSetInfo and the value for the source is in expRms. This is subtracted from the rms in quadrature to get the intrinsic rms: the variability of the object beyond the noise in the system. The chisquared is calculated, assuming a nonvariable object which has the noise from the expectedrms and mean calculated as above. The probVar statistic assumes a chisquared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3. 
yMagMAD 
vmcVariability 