WSA Browser

Glossary of WSA NonSurvey attributes (UKIDSSDR10)

This Glossary alphabetically lists all attributes used in the WSA NonSurvey database(s) held in the WSA. If you would like to have more information about the schema tables please use the Schema Browser (other Browser versions).

A B C D E F G H I J K L M
N O P Q R S T U V W X Y Z

N

Name Schema Table Database Description Type Length Unit Default Value Unified Content Descriptor

name [nspid]FSstars WSA NonSurvey reference name of field varchar 16 NONE ????

name [nspid]Filter WSA NonSurvey The name of the filter, eg. "MKO J", "WFCAM Y" etc. varchar 16 meta.note

name [nspid]RequiredMatchedApertureProduct WSA NonSurvey the name of the matched aperture product varchar 16 ??

name [nspid]RequiredMosaic WSA NonSurvey Name of the mosaiced product varchar 64 ??

name [nspid]RequiredMosaicTopLevel WSA NonSurvey Name of the mosaiced product set up varchar 64 ??

name [nspid]RequiredRegion WSA NonSurvey Name of the region varchar 64 ??

name [nspid]RequiredStack WSA NonSurvey Name of the stacked product varchar 64 ??

name [nspid]Survey WSA NonSurvey The short name for the survey varchar 128 ??

nbhAperMag3 [nspid]Source WSA NonSurvey Default point source Nbh aperture corrected mag (2.0 arcsec aperture diameter)
If in doubt use this flux estimator real 4 mag -0.9999995e9 PHOT_MAG

nbhAperMag3Err [nspid]Source WSA NonSurvey Error in default point source Nbh mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbhAperMag4 [nspid]Source WSA NonSurvey Point source Nbh aperture corrected mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbhAperMag4Err [nspid]Source WSA NonSurvey Error in point source Nbh mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbhAperMag6 [nspid]Source WSA NonSurvey Point source Nbh aperture corrected mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbhAperMag6Err [nspid]Source WSA NonSurvey Error in point source Nbh mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbhaStratAst [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c0 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbhaStratPht [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c0 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbhbestAper [nspid]Variability WSA NonSurvey Best aperture (1-6) for photometric statistics in the Nbh band int 4 -9999

Aperture magnitude (1-6) 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)

nbhbStratAst [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c1 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbhbStratPht [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c1 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbhchiSqAst [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to astrometric data in Nbh band real 4 -0.9999995e9 stat.fit.goodness

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbhchiSqpd [nspid]Variability WSA NonSurvey 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhchiSqPht [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to photometric data in Nbh 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbhClass [nspid]Source WSA NonSurvey discrete image classification flag in Nbh smallint 2 -9999 CLASS_MISC

nbhClassStat [nspid]Source WSA NonSurvey N(0,1) stellarness-of-profile statistic in Nbh real 4 -0.9999995e9 STAT_PROP

nbhcStratAst [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c2 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbhcStratPht [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c2 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbhDeblend [nspid]Source WSA NonSurvey placeholder flag indicating parent/child relation in Nbh int 4 -99999999 CODE_MISC

This CASU pipeline processing source extraction flag is a placeholder only, and is always set to zero in all passbands in the merged source lists. If you need to know when a particular image detection is a component of a deblend or not, test bit 4 of attribute ppErrBits (see corresponding glossary entry) which is set by WFAU's post-processing software based on testing the areal profiles aprof2-8 (these are set by CASU to -1 for deblended components, or positive values for non-deblended detections). We encode this in an information bit of ppErrBits for convenience when querying the merged source tables.

nbhdStratAst [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c3 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to astrometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbhdStratPht [nspid]VarFrameSetInfo WSA NonSurvey Parameter, c0 from Ferreira-Lopes & Cross 2017, Eq. 18, in fit to photometric rms vs magnitude in Nbh band. real 4 -0.9999995e9 stat.fit.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbhEll [nspid]Source WSA NonSurvey 1-b/a, where a/b=semi-major/minor axes in Nbh real 4 -0.9999995e9 PHYS_ELLIPTICITY

nbheNum [nspid]MergeLog WSA NonSurvey the extension number of this Nbh frame tinyint 1 NUMBER

nbhErrBits [nspid]Source WSA NonSurvey processing warning/error bitwise flags in Nbh int 4 -99999999 CODE_MISC

Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture.

nbhEta [nspid]Source WSA NonSurvey Offset of Nbh detection from master position (+north/-south) real 4 arcsec -0.9999995e9 POS_EQ_DEC_OFF

When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; UHS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. 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 LAS, you might wish to insist that the offsets in the selected sample are all below 1 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.

nbhexpML [nspid]VarFrameSetInfo WSA NonSurvey Expected magnitude limit of frameSet in this in Nbh band. real 4 -0.9999995e9

The expected magnitude limit of an intermediate stack, based on the total exposure time. expML=Filter.oneSecML+1.25*log10(totalExpTime). Since different intermediate stacks can have different exposure times, the totalExpTime is the minimum, as long as the number of stacks with this minimum make up 10% of the total. This is a more conservative treatment than just taking the mean or median total exposure time.

nbhExpRms [nspid]Variability WSA NonSurvey Rms calculated from polynomial fit to modal RMS as a function of magnitude in Nbh 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhGausig [nspid]Source WSA NonSurvey RMS of axes of ellipse fit in Nbh real 4 pixels -0.9999995e9 MORPH_PARAM

nbhHallMag [nspid]Source WSA NonSurvey Total point source Nbh mag real 4 mag -0.9999995e9 PHOT_MAG

nbhHallMagErr [nspid]Source WSA NonSurvey Error in total point source Nbh mag real 4 mag -0.9999995e9 ERROR

nbhIntRms [nspid]Variability WSA NonSurvey Intrinsic rms in Nbh-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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhisDefAst [nspid]VarFrameSetInfo WSA NonSurvey Use a default model for the astrometric noise in Nbh band. tinyint 1 0 meta.code

nbhisDefPht [nspid]VarFrameSetInfo WSA NonSurvey Use a default model for the photometric noise in Nbh band. tinyint 1 0

nbhMagMAD [nspid]Variability WSA NonSurvey Median Absolute Deviation of Nbh 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhMagRms [nspid]Variability WSA NonSurvey rms of Nbh 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhmaxCadence [nspid]Variability WSA NonSurvey maximum gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhMaxMag [nspid]Variability WSA NonSurvey Maximum magnitude in Nbh band, of good detections 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhmeanMag [nspid]Variability WSA NonSurvey Mean Nbh 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhmedCadence [nspid]Variability WSA NonSurvey median gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhmedianMag [nspid]Variability WSA NonSurvey Median Nbh 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhmfID [nspid]MergeLog WSA NonSurvey the UID of the relevant Nbh multiframe bigint 8 ID_FRAME

nbhminCadence [nspid]Variability WSA NonSurvey minimum gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhMinMag [nspid]Variability WSA NonSurvey Minimum magnitude in Nbh band, of good detections 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhndof [nspid]Variability WSA NonSurvey Number of degrees of freedom for chisquare smallint 2 -9999

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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhnDofAst [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of astrometric fit in Nbh band. smallint 2 -9999 stat.fit.dof;stat.param

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbhnDofPht [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of photometric fit in Nbh band. smallint 2 -9999

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbhnFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Nbh band flagged as potentially spurious by u10b11Detection.ppErrBits int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhnFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Nbh band flagged as potentially spurious by u12ak3Detection.ppErrBits int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhnGoodObs [nspid]Variability WSA NonSurvey Number of good detections in Nbh band int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhNgt3sig [nspid]Variability WSA NonSurvey Number of good detections in Nbh-band that are more than 3 sigma deviations (nbhAperMagN < (nbhMeanMag-3*nbhMagRms) smallint 2 -9999

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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhnMissingObs [nspid]Variability WSA NonSurvey Number of Nbh band frames that this object should have been detected on and was not int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhPA [nspid]Source WSA NonSurvey ellipse fit celestial orientation in Nbh real 4 Degrees -0.9999995e9 POS_POS-ANG

nbhPetroMag [nspid]Source WSA NonSurvey Extended source Nbh mag (Petrosian) real 4 mag -0.9999995e9 PHOT_MAG

nbhPetroMagErr [nspid]Source WSA NonSurvey Error in extended source Nbh mag (Petrosian) real 4 mag -0.9999995e9 ERROR

nbhppErrBits [nspid]Source WSA NonSurvey additional WFAU post-processing error bits in Nbh int 4 0 CODE_MISC

Post-processing error quality bit flags assigned (NB: from UKIDSS DR2 release onwards) in the WSA curation procedure for survey data. From least to most significant byte in the 4-byte integer attribute byte 0 (bits 0 to 7) corresponds to information on generally innocuous conditions that are nonetheless potentially significant as regards the integrity of that detection; byte 1 (bits 8 to 15) corresponds to warnings; byte 2 (bits 16 to 23) corresponds to important warnings; and finally byte 3 (bits 24 to 31) corresponds to severe warnings:

Byte Bit Detection quality issue Threshold or bit mask Applies to

Decimal Hexadecimal

0 4 Deblended 16 0x00000010 All VDFS catalogues

0 6 Bad pixel(s) in default aperture 64 0x00000040 All VDFS catalogues

1 15 Source in poor flat field region 32768 0x00008000 All but mosaics

2 16 Close to saturated 65536 0x00010000 All VDFS catalogues (though deeps excluded prior to DR8)

2 17 Photometric calibration probably subject to systematic error 131072 0x00020000 GPS only

2 19 Possible crosstalk artefact/contamination 524288 0x00080000 All but GPS

2 22 Lies within a dither offset of the stacked frame boundary 4194304 0x00400000 All but mosaics

In this way, the higher the error quality bit flag value, the more likely it is that the detection is spurious. The decimal threshold (column 4) gives the minimum value of the quality flag for a detection having the given condition (since other bits in the flag may be set also; the corresponding hexadecimal value, where each digit corresponds to 4 bits in the flag, can be easier to compute when writing SQL queries to test for a given condition). For example, to exclude all K band sources in the LAS having any error quality condition other than informational ones, include a predicate ... AND kppErrBits ≤ 255. See the SQL Cookbook and other online pages for further information.

nbhprobVar [nspid]Variability WSA NonSurvey Probability of variable from chi-square (and other data) 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhPsfMag [nspid]Source WSA NonSurvey Point source profile-fitted Nbh mag real 4 mag -0.9999995e9 PHOT_MAG

nbhPsfMagErr [nspid]Source WSA NonSurvey Error in point source profile-fitted Nbh mag real 4 mag -0.9999995e9 ERROR

nbhSeqNum [nspid]Source WSA NonSurvey the running number of the Nbh detection int 4 -99999999 ID_NUMBER

nbhSerMag2D [nspid]Source WSA NonSurvey Extended source Nbh mag (profile-fitted) real 4 mag -0.9999995e9 PHOT_MAG

nbhSerMag2DErr [nspid]Source WSA NonSurvey Error in extended source Nbh mag (profile-fitted) real 4 mag -0.9999995e9 ERROR

nbhskewness [nspid]Variability WSA NonSurvey Skewness in Nbh band (see Sesar et al. 2007) 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhtotalPeriod [nspid]Variability WSA NonSurvey total period of observations (last obs-first obs) real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbhVarClass [nspid]Variability WSA NonSurvey Classification of variability in this band smallint 2 -9999

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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbhXi [nspid]Source WSA NonSurvey Offset of Nbh detection from master position (+east/-west) real 4 arcsec -0.9999995e9 POS_EQ_RA_OFF

When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; UHS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. 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 LAS, you might wish to insist that the offsets in the selected sample are all below 1 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.

nbjAperMag1 [nspid]SynopticSource WSA NonSurvey Extended source Nbj aperture corrected mag (0.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag1Err [nspid]SynopticSource WSA NonSurvey Error in extended source Nbj mag (0.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag2 [nspid]SynopticSource WSA NonSurvey Extended source Nbj aperture corrected mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag2Err [nspid]SynopticSource WSA NonSurvey Error in extended source Nbj mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag3 [nspid]Source WSA NonSurvey Default point/extended source Nbj aperture corrected mag (2.0 arcsec aperture diameter)
If in doubt use this flux estimator real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag3 [nspid]SynopticSource WSA NonSurvey Default point/extended source Nbj aperture corrected mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag3Err [nspid]Source, [nspid]SynopticSource WSA NonSurvey Error in default point/extended source Nbj mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag4 [nspid]Source, [nspid]SynopticSource WSA NonSurvey Extended source Nbj aperture corrected mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag4Err [nspid]Source, [nspid]SynopticSource WSA NonSurvey Error in extended source Nbj mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag5 [nspid]SynopticSource WSA NonSurvey Extended source Nbj aperture corrected mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag5Err [nspid]SynopticSource WSA NonSurvey Error in extended source Nbj mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjAperMag6 [nspid]Source WSA NonSurvey Extended source Nbj aperture corrected mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

nbjAperMag6Err [nspid]Source WSA NonSurvey Error in extended source Nbj mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

nbjaStratAst [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, a, in fit to astrometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbjaStratPht [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, a, in fit to photometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjbestAper [nspid]Variability WSA NonSurvey Best aperture (1-6) for photometric statistics in the Nbj band int 4 -9999

Aperture magnitude (1-6) 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)

nbjbStratAst [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, b, in fit to astrometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbjbStratPht [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, b, in fit to photometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjchiSqAst [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to astrometric data in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbjchiSqpd [nspid]Variability WSA NonSurvey 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjchiSqPht [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to photometric data in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjClass [nspid]Source, [nspid]SynopticSource WSA NonSurvey discrete image classification flag in Nbj smallint 2 -9999 CLASS_MISC

nbjClassStat [nspid]Source, [nspid]SynopticSource WSA NonSurvey N(0,1) stellarness-of-profile statistic in Nbj real 4 -0.9999995e9 STAT_PROP

nbjcStratAst [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, c, in fit to astrometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbjcStratPht [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, c, in fit to photometric rms vs magnitude in Nbj 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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjDeblend [nspid]Source WSA NonSurvey placeholder flag indicating parent/child relation in Nbj int 4 -99999999 CODE_MISC

This CASU pipeline processing source extraction flag is a placeholder only, and is always set to zero in all passbands in the merged source lists. If you need to know when a particular image detection is a component of a deblend or not, test bit 4 of attribute ppErrBits (see corresponding glossary entry) which is set by WFAU's post-processing software based on testing the areal profiles aprof2-8 (these are set by CASU to -1 for deblended components, or positive values for non-deblended detections). We encode this in an information bit of ppErrBits for convenience when querying the merged source tables.

nbjDeblend [nspid]SynopticSource WSA NonSurvey placeholder flag indicating parent/child relation in Nbj int 4 -99999999 CODE_MISC

nbjEll [nspid]Source, [nspid]SynopticSource WSA NonSurvey 1-b/a, where a/b=semi-major/minor axes in Nbj real 4 -0.9999995e9 PHYS_ELLIPTICITY

nbjeNum [nspid]MergeLog, [nspid]SynopticMergeLog WSA NonSurvey the extension number of this Nbj frame tinyint 1 NUMBER

nbjErrBits [nspid]Source, [nspid]SynopticSource WSA NonSurvey processing warning/error bitwise flags in Nbj int 4 -99999999 CODE_MISC

Apparently not actually an error bit flag, but a count of the number of zero confidence pixels in the default (2 arcsec diameter) aperture.

nbjEta [nspid]Source, [nspid]SynopticSource WSA NonSurvey Offset of Nbj detection from master position (+north/-south) real 4 arcsec -0.9999995e9 POS_EQ_DEC_OFF

When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; UHS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. 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 LAS, you might wish to insist that the offsets in the selected sample are all below 1 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.

nbjexpML [nspid]VarFrameSetInfo WSA NonSurvey Expected magnitude limit of frameSet in this in Nbj band. real 4 -0.9999995e9

The expected magnitude limit of an intermediate stack, based on the total exposure time. expML=Filter.oneSecML+1.25*log10(totalExpTime). Since different intermediate stacks can have different exposure times, the totalExpTime is the minimum, as long as the number of stacks with this minimum make up 10% of the total. This is a more conservative treatment than just taking the mean or median total exposure time.

nbjExpRms [nspid]Variability WSA NonSurvey Rms calculated from polynomial fit to modal RMS as a function of magnitude in Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjGausig [nspid]Source, [nspid]SynopticSource WSA NonSurvey RMS of axes of ellipse fit in Nbj real 4 pixels -0.9999995e9 MORPH_PARAM

nbjHallMag [nspid]Source WSA NonSurvey Total point source Nbj mag real 4 mag -0.9999995e9 PHOT_MAG

nbjHallMagErr [nspid]Source WSA NonSurvey Error in total point source Nbj mag real 4 mag -0.9999995e9 ERROR

nbjIntRms [nspid]Variability WSA NonSurvey Intrinsic rms in Nbj-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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjisDefAst [nspid]VarFrameSetInfo WSA NonSurvey Use a default model for the astrometric noise in Nbj band. tinyint 1 0

nbjisDefPht [nspid]VarFrameSetInfo WSA NonSurvey Use a default model for the photometric noise in Nbj band. tinyint 1 0

nbjMagMAD [nspid]Variability WSA NonSurvey Median Absolute Deviation of Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjMagRms [nspid]Variability WSA NonSurvey rms of Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmaxCadence [nspid]Variability WSA NonSurvey maximum gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjMaxMag [nspid]Variability WSA NonSurvey Maximum magnitude in Nbj band, of good detections 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmeanMag [nspid]Variability WSA NonSurvey Mean Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmedCadence [nspid]Variability WSA NonSurvey median gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjmedianMag [nspid]Variability WSA NonSurvey Median Nbj 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmfID [nspid]MergeLog, [nspid]SynopticMergeLog WSA NonSurvey the UID of the relevant Nbj multiframe bigint 8 ID_FRAME

nbjminCadence [nspid]Variability WSA NonSurvey minimum gap between observations real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjMinMag [nspid]Variability WSA NonSurvey Minimum magnitude in Nbj band, of good detections 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjmjExt [nspid]Source WSA NonSurvey Extended source colour Nbj-J (using aperMag3) real 4 mag -0.9999995e9 PHOT_COLOR

Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.

nbjmjExtErr [nspid]Source WSA NonSurvey Error on extended source colour Nbj-J real 4 mag -0.9999995e9 ERROR

Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.

nbjmjPnt [nspid]Source, [nspid]SynopticSource WSA NonSurvey Point source colour Nbj-J (using aperMag3) real 4 mag -0.9999995e9 PHOT_COLOR

Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.

nbjmjPntErr [nspid]Source, [nspid]SynopticSource WSA NonSurvey Error on point source colour Nbj-J real 4 mag -0.9999995e9 ERROR

Default colours from pairs of adjacent passbands within a given set (e.g. Y-J, J-H and H-K for YJHK) are recorded in the merged source table for ease of querying and speedy querying via indexing of these attributes. Presently, the point-source colours and extended source colours are computed from the aperture corrected AperMag3 fixed 2 arcsec aperture diameter measures (for consistent measurement across all passbands) and generally good signal-to-noise. At some point in the future, this may be changed such that point-source colours will be computed from the PSF-fitted measures and extended source colours computed from the 2-d Sersic model profile fits.

nbjndof [nspid]Variability WSA NonSurvey Number of degrees of freedom for chisquare smallint 2 -9999

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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjnDofAst [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of astrometric fit in Nbj band. smallint 2 -9999

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated.

nbjnDofPht [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of photometric fit in Nbj band. smallint 2 -9999

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 median-absolute 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 chi-squared and number of degrees of freedom are also calculated. This technique was used in Sesar et al. 2007, AJ, 134, 2236.

nbjnFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Nbj band flagged as potentially spurious by calDetection.ppErrBits int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjnGoodObs [nspid]Variability WSA NonSurvey Number of good detections in Nbj band int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjNgt3sig [nspid]Variability WSA NonSurvey Number of good detections in Nbj-band that are more than 3 sigma deviations smallint 2 -9999

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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjnMissingObs [nspid]Variability WSA NonSurvey Number of Nbj band frames that this object should have been detected on and was not int 4 0

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjPA [nspid]Source, [nspid]SynopticSource WSA NonSurvey ellipse fit celestial orientation in Nbj real 4 Degrees -0.9999995e9 POS_POS-ANG

nbjPetroMag [nspid]Source WSA NonSurvey Extended source Nbj mag (Petrosian) real 4 mag -0.9999995e9 PHOT_MAG

nbjPetroMagErr [nspid]Source WSA NonSurvey Error in extended source Nbj mag (Petrosian) real 4 mag -0.9999995e9 ERROR

nbjppErrBits [nspid]Source, [nspid]SynopticSource WSA NonSurvey additional WFAU post-processing error bits in Nbj int 4 0 CODE_MISC

Post-processing error quality bit flags assigned (NB: from UKIDSS DR2 release onwards) in the WSA curation procedure for survey data. From least to most significant byte in the 4-byte integer attribute byte 0 (bits 0 to 7) corresponds to information on generally innocuous conditions that are nonetheless potentially significant as regards the integrity of that detection; byte 1 (bits 8 to 15) corresponds to warnings; byte 2 (bits 16 to 23) corresponds to important warnings; and finally byte 3 (bits 24 to 31) corresponds to severe warnings:

Byte Bit Detection quality issue Threshold or bit mask Applies to

Decimal Hexadecimal

0 4 Deblended 16 0x00000010 All VDFS catalogues

0 6 Bad pixel(s) in default aperture 64 0x00000040 All VDFS catalogues

1 15 Source in poor flat field region 32768 0x00008000 All but mosaics

2 16 Close to saturated 65536 0x00010000 All VDFS catalogues (though deeps excluded prior to DR8)

2 17 Photometric calibration probably subject to systematic error 131072 0x00020000 GPS only

2 19 Possible crosstalk artefact/contamination 524288 0x00080000 All but GPS

2 22 Lies within a dither offset of the stacked frame boundary 4194304 0x00400000 All but mosaics

In this way, the higher the error quality bit flag value, the more likely it is that the detection is spurious. The decimal threshold (column 4) gives the minimum value of the quality flag for a detection having the given condition (since other bits in the flag may be set also; the corresponding hexadecimal value, where each digit corresponds to 4 bits in the flag, can be easier to compute when writing SQL queries to test for a given condition). For example, to exclude all K band sources in the LAS having any error quality condition other than informational ones, include a predicate ... AND kppErrBits ≤ 255. See the SQL Cookbook and other online pages for further information.

nbjprobVar [nspid]Variability WSA NonSurvey Probability of variable from chi-square (and other data) 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjPsfMag [nspid]Source WSA NonSurvey Point source profile-fitted Nbj mag real 4 mag -0.9999995e9 PHOT_MAG

nbjPsfMagErr [nspid]Source WSA NonSurvey Error in point source profile-fitted Nbj mag real 4 mag -0.9999995e9 ERROR

nbjSeqNum [nspid]Source, [nspid]SynopticSource WSA NonSurvey the running number of the Nbj detection int 4 -99999999 ID_NUMBER

nbjSerMag2D [nspid]Source WSA NonSurvey Extended source Nbj mag (profile-fitted) real 4 mag -0.9999995e9 PHOT_MAG

nbjSerMag2DErr [nspid]Source WSA NonSurvey Error in extended source Nbj mag (profile-fitted) real 4 mag -0.9999995e9 ERROR

nbjskewness [nspid]Variability WSA NonSurvey Skewness in Nbj band (see Sesar et al. 2007) 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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjtotalPeriod [nspid]Variability WSA NonSurvey total period of observations (last obs-first obs) real 4 days -0.9999995e9

The observations are classified as good, flagged or missing. Flagged observations are ones where the object has a ppErrBit flag. Missing observations are observations of the part of the sky that include the position of the object, but had no detection. All the statistics are calculated from good observations. The cadence parameters give the minimum, median and maximum time between observations, which is useful to know if the data could be used to find a particular type of variable.

nbjVarClass [nspid]Variability WSA NonSurvey Classification of variability in this band smallint 2 -9999

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 chi-squared is calculated, assuming a non-variable object which has the noise from the expected-rms and mean calculated as above. The probVar statistic assumes a chi-squared distribution with the correct number of degrees of freedom. The varClass statistic is 1, if the probVar>0.9 and intrinsicRMS/expectedRMS>3.

nbjXi [nspid]Source, [nspid]SynopticSource WSA NonSurvey Offset of Nbj detection from master position (+east/-west) real 4 arcsec -0.9999995e9 POS_EQ_RA_OFF

When associating individual passband detections into merged sources, a generous (in terms of the positional uncertainties) pairing radius of 2.0 (UKIDSS LAS and GPS; UHS; also non-survey programmes) or 1.0 (UKIDSS GPS, DXS and UDS) arcseconds is used, the higher value enabling pairing of moving sources when epoch separations may be several years. 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 LAS, you might wish to insist that the offsets in the selected sample are all below 1 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.

nDof [nspid]SatelliteOrbits WSA NonSurvey Number of degrees of freedom of fit int 4

neighboursSchema [nspid]Programme WSA NonSurvey Script file that describes the neighbour tables schema for this programme varchar 64 ??

neighbourTable [nspid]RequiredNeighbours WSA NonSurvey the name of the neighbour join table varchar 256 meta.id;meta.dataset

nEpochs [nspid]RequiredMapAverages WSA NonSurvey Number of frames to average over int 4 -99999999

newBrframe [nspid]MergeLog, [nspid]SynopticMergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newFeiiframe [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newFrameSet [nspid]JHKmergeLog, [nspid]JKmergeLog, [nspid]MergeLog, [nspid]SynopticMergeLog, [nspid]YJHKmergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey Flag used internally by curation applications tinyint 1 CODE_MISC

newH2_1frame [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newH2_2frame [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newH2frame [nspid]JHKmergeLog, [nspid]MergeLog, [nspid]SynopticMergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newHframe [nspid]JHKmergeLog, [nspid]JKmergeLog, [nspid]MergeLog, [nspid]SynopticMergeLog, [nspid]YJHKmergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJ_1frame [nspid]MergeLog, [nspid]YJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJ_2frame [nspid]MergeLog, [nspid]YJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJ_3frame [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJ_4frame [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newJframe [nspid]JHKmergeLog, [nspid]JKmergeLog, [nspid]MergeLog, [nspid]SynopticMergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newK_1frame [nspid]JHKmergeLog, [nspid]MergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newK_2frame [nspid]JHKmergeLog, [nspid]MergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newKframe [nspid]JKmergeLog, [nspid]MergeLog, [nspid]SynopticMergeLog, [nspid]YJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newlyIngested [nspid]Multiframe WSA NonSurvey Curation flag for internal use only (0=no, 1=yes) tinyint 1 1 ??

newNbhframe [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newNbjframe [nspid]MergeLog, [nspid]SynopticMergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newY_1frame [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newY_2frame [nspid]MergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newYframe [nspid]MergeLog, [nspid]SynopticMergeLog, [nspid]YJHKmergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

newZframe [nspid]MergeLog, [nspid]SynopticMergeLog, [nspid]ZYJHKmergeLog WSA NonSurvey new/old flag (1/0) of this detector image tinyint 1 CODE_MISC

nFoc [nspid]Multiframe WSA NonSurvey Number of positions in focus scan {image primary HDU keyword: NFOC} smallint 2 -9999 meta.number

nFocScan [nspid]Multiframe WSA NonSurvey Number of focus scans in focus test {image primary HDU keyword: NFOCSCAN} smallint 2 -9999 meta.number

nFrames [nspid]ExtendedSource, [nspid]GcsPointSource, [nspid]GpsPointSource, [nspid]JHKsource, [nspid]LasPointSource, [nspid]PointSource, [nspid]Source, [nspid]YJHKsource, [nspid]ZYJHKsource WSA NonSurvey No. of frames used for this proper motion measurement tinyint 1 0 NUMBER

nFrames [nspid]Variability WSA NonSurvey Number of frames with good detections used to calculate astrometric fits int 4 0 NUMBER

The Variability table contains statistics from the set of observations of each source. At present, the mean ra and dec and the error in two tangential directions are calculated. The "ra" direction is defined as tangential to both the radial direction and the cartesian z-axis and the "dec" direction is defined as both the radial direction and the "ra" direction. Since the current model is just the mean and standard deviation of the data, then the chi-squared of the fit=1. Data from good frames across all bands go into the astrometric model determination. This will include bands in non-synoptic filters: the one observation in these bands can help. In future releases a fit will be made to the rms data as a function of magnitude in each band, as has already happened for photometric data and a motion model that incorporates proper motion (and possibly parallax) will be used. The motion model is a parameter in the VarFrameSetInfo table.

nightZPCat [nspid]MultiframeDetector WSA NonSurvey Average photometric zero point for night {catalogue extension keyword: NIGHTZPT} real 4 mags -0.9999995e9 ??

nightZPCat [nspid]PreviousMFDZP WSA NonSurvey Average photometric zero point for night real 4 mags -0.9999995e9 ??

nightZPErrCat [nspid]MultiframeDetector WSA NonSurvey Photometric zero point sigma for night {catalogue extension keyword: NIGHTZRR}
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPErrCat [nspid]PreviousMFDZP WSA NonSurvey Photometric zero point sigma for night
<0.05 mags for a good night real 4 mags -0.9999995e9 ??

nightZPNum [nspid]MultiframeDetector WSA NonSurvey Number of ZP in band used to calculate nightZPCat {catalogue extension keyword: NIGHTNUM} int 4 mags -99999999 ??

nightZPNum [nspid]PreviousMFDZP WSA NonSurvey Number of ZP in band used to calculate nightZPCat int 4 mags -99999999 ??

nInFrameset [nspid]MapRemeasAver WSA NonSurvey Number of frames in the frameSet linked in MapProvenance int 4

njitter [nspid]Multiframe WSA NonSurvey Number of positions in telescope pattern {image primary HDU keyword: NJITTER} smallint 2 -9999 meta.number

nMeasurements [nspid]MapRemeasAver WSA NonSurvey Number used in average. int 4

nonperp [nspid]AstrometricInfo WSA NonSurvey Non-perpendicularity of axes float 8 degrees -0.9999995e9 ??

nonperp [nspid]AstrometricInfo WSA NonSurvey Non-perpendicularity of axes float 8 radians -0.9999995e9 ??

normSoft [nspid]MapCatalogueDetector WSA NonSurvey Normalised softening parameter (averaged for tiles) for luptitude calculation {catalogue TType keyword: NORMSOFT} float 8

nPass [nspid]RequiredFilters WSA NonSurvey the number of passes that will be made smallint 2 meta.number

nPix [nspid]SatelliteDetection WSA NonSurvey No. of pixels above threshold int 4 pixels NUMBER

nTrails [nspid]SatelliteOrbits WSA NonSurvey Number of satellite trails used to compute the orbit int 4

numAxes [nspid]MultiframeDetector WSA NonSurvey Number of data axes; eg. 2 tinyint 1 meta.number

numberStk [nspid]RequiredStack WSA NonSurvey Number of intermediate stacks. If default, stack all good quality stacks int 4 -99999999

numDetectors [nspid]Multiframe WSA NonSurvey The number of "detectors" (=image extensions in FITS file) tinyint 1 ??

numExp [nspid]Multiframe WSA NonSurvey Number of exposures in integration {image primary HDU keyword: NEXP} smallint 2 -9999 meta.number

numInts [nspid]Multiframe WSA NonSurvey Number of integrations in observation {image primary HDU keyword: NINT} smallint 2 meta.number

numReads [nspid]Multiframe WSA NonSurvey Number of reads per exposure {image primary HDU keyword: NREADS} smallint 2 -9999 meta.number

numRms [nspid]CurrentAstrometry, [nspid]PreviousAstrometry WSA NonSurvey No. of astrometric standards used in fit {image extension keyword: NUMBRMS} int 4 -99999999 stat.fit.param

numZPCat [nspid]MultiframeDetector WSA NonSurvey Number of standards used in determining photZPCat and photZPCatErr {catalogue extension keyword: NUMZPT} int 4 -99999999

numZPCat [nspid]PreviousMFDZP WSA NonSurvey Number of standards used in determining photZP and photZPErr int 4 -99999999

nuStep [nspid]Multiframe WSA NonSurvey Number of positions in microstep pattern {image primary HDU keyword: NUSTEP} smallint 2 -9999 meta.number

nustep [nspid]RequiredMosaic, [nspid]RequiredStack WSA NonSurvey Amount of microstepping tinyint 1 ??

WFAU, Institute for Astronomy,
Royal Observatory, Blackford Hill
Edinburgh, EH9 3HJ, UK

wsa-support@roe.ac.uk
29/06/2018