WSA Browser

Glossary of WSA NonSurvey attributes (UKIDSSDR11)

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

Z

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

z11 [nspid]Multiframe WSA NonSurvey Spherical: Z11 {image primary HDU keyword: Z11} real 4 -0.9999995e9

z7 [nspid]Multiframe WSA NonSurvey Coma: Z7 {image primary HDU keyword: Z7} real 4 -0.9999995e9

z8 [nspid]Multiframe WSA NonSurvey Coma: Z8 {image primary HDU keyword: Z8} real 4 -0.9999995e9

zAperMag1 [nspid]SynopticSource WSA NonSurvey Extended source Z aperture corrected mag (1.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag1Err [nspid]SynopticSource WSA NonSurvey Error in extended source Z mag (1.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag2 [nspid]SynopticSource WSA NonSurvey Extended source Z aperture corrected mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag2Err [nspid]SynopticSource WSA NonSurvey Error in extended source Z mag (1.4 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag3 [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Default point source Z aperture corrected mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag3 [nspid]Source WSA NonSurvey Default point/extended source Z aperture corrected mag (2.0 arcsec aperture diameter)
If in doubt use this flux estimator real 4 mag -0.9999995e9 PHOT_MAG

zAperMag3 [nspid]Source WSA NonSurvey Default point source Z aperture corrected mag (2.0 arcsec aperture diameter)
If in doubt use this flux estimator real 4 mag -0.9999995e9 PHOT_MAG

zAperMag3 [nspid]SynopticSource WSA NonSurvey Default point/extended source Z aperture corrected mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag3Err [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in default point source Z mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag3Err [nspid]Source, [nspid]SynopticSource WSA NonSurvey Error in default point/extended source Z mag (2.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag4 [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Point source Z aperture corrected mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag4 [nspid]Source, [nspid]SynopticSource WSA NonSurvey Extended source Z aperture corrected mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag4Err [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in point source Z mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag4Err [nspid]Source, [nspid]SynopticSource WSA NonSurvey Error in extended source Z mag (2.8 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag5 [nspid]SynopticSource WSA NonSurvey Extended source Z aperture corrected mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag5Err [nspid]SynopticSource WSA NonSurvey Error in extended source Z mag (4.0 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag6 [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Point source Z aperture corrected mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag6 [nspid]Source WSA NonSurvey Extended source Z aperture corrected mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 PHOT_MAG

zAperMag6Err [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in point source Z mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zAperMag6Err [nspid]Source WSA NonSurvey Error in extended source Z mag (5.7 arcsec aperture diameter) real 4 mag -0.9999995e9 ERROR

zaStratAst [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, a, in fit to astrometric rms vs magnitude in Z 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.

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

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.

zaStratPht [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Strateva parameter, a, in fit to photometric rms vs magnitude in Z band, see Sesar et al. 2007. real 4 -0.9999995e9 stat.fit.param;em.opt.I

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.

zaStratPht [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, a, in fit to photometric rms vs magnitude in Z 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.

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

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.

zbestAper [nspid]QsoMapVariability WSA NonSurvey Best aperture (1-3) for photometric statistics in the Z 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)

zbestAper [nspid]Variability WSA NonSurvey Best aperture (1-6) for photometric statistics in the Z 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)

zbStratAst [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, b, in fit to astrometric rms vs magnitude in Z 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.

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

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.

zbStratPht [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Strateva parameter, b, in fit to photometric rms vs magnitude in Z band, see Sesar et al. 2007. real 4 -0.9999995e9 stat.fit.param;em.opt.I

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.

zbStratPht [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, b, in fit to photometric rms vs magnitude in Z 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.

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

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.

zchiSqAst [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to astrometric data in Z 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.

zchiSqAst [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to astrometric data in Z band real 4 -0.9999995e9 stat.fit.goodness;em.opt.I

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.

zchiSqpd [nspid]QsoMapVariability, [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.

zchiSqPht [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to photometric data in Z band real 4 -0.9999995e9 stat.fit.goodness;em.opt.I

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.

zchiSqPht [nspid]VarFrameSetInfo WSA NonSurvey Goodness of fit of Strateva function to photometric data in Z 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.

zClass [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey discrete image classification flag in Z smallint 2 -9999 CLASS_MISC

zClassStat [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey N(0,1) stellarness-of-profile statistic in Z real 4 -0.9999995e9 STAT_PROP

zcStratAst [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, c, in fit to astrometric rms vs magnitude in Z 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.

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

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.

zcStratPht [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Strateva parameter, c, in fit to photometric rms vs magnitude in Z band, see Sesar et al. 2007. real 4 -0.9999995e9 stat.fit.param;em.opt.I

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.

zcStratPht [nspid]VarFrameSetInfo WSA NonSurvey Strateva parameter, c, in fit to photometric rms vs magnitude in Z 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.

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

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.

zDeblend [nspid]GcsPointSource, [nspid]PointSource, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey placeholder flag indicating parent/child relation in Z int 4 -99999999 CODE_MISC

zDeblend [nspid]Source WSA NonSurvey placeholder flag indicating parent/child relation in Z 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.

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

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.

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

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.

zEll [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey 1-b/a, where a/b=semi-major/minor axes in Z real 4 -0.9999995e9 PHYS_ELLIPTICITY

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

zeNum [nspid]ZYJHKmergeLog WSA NonSurvey the extension number of this frame tinyint 1 NUMBER

zeroPoint [nspid]ExternalProduct WSA NonSurvey Zeropoint of each product real 4 -0.9999995e9

zeropoint [nspid]RequiredMosaicTopLevel WSA NonSurvey Zeropoint of each product real 4 -0.9999995e9

zErrBits [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey processing warning/error bitwise flags in Z int 4 -99999999 CODE_MISC

zErrBits [nspid]Source, [nspid]SynopticSource WSA NonSurvey processing warning/error bitwise flags in Z 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.

zEta [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Offset of Z detection from master position (+north/-south) real 4 arcsec -0.9999995e9 POS_EQ_DEC_OFF

zEta [nspid]Source, [nspid]SynopticSource WSA NonSurvey Offset of Z 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.

zexpML [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Expected magnitude limit of frameSet in this in Z band. real 4 mag -0.9999995e9 phot.mag;em.opt.I;stat.max

zexpML [nspid]VarFrameSetInfo WSA NonSurvey Expected magnitude limit of frameSet in this in Z 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.

zExpRms [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Rms calculated from polynomial fit to modal RMS as a function of magnitude in Z 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.

zGausig [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey RMS of axes of ellipse fit in Z real 4 pixels -0.9999995e9 MORPH_PARAM

zHallMag [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Total point source Z mag real 4 mag -0.9999995e9 PHOT_MAG

zHallMagErr [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in total point source Z mag real 4 mag -0.9999995e9 ERROR

zIntRms [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Intrinsic rms in Z-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.

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

zisDefAst [nspid]VarFrameSetInfo WSA NonSurvey Use a default model for the astrometric noise in Z band. tinyint 1 0 meta.code;em.opt.I

zisDefPht [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Use a default model for the photometric noise in Z band. tinyint 1 0 meta.code;em.opt.I

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

zMagMAD [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Median Absolute Deviation of Z 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.

zMagRms [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey rms of Z 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.

zmaxCadence [nspid]QsoMapVariability, [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.

zMaxMag [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Maximum magnitude in Z 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.

zmeanMag [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Mean Z 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.

zmedCadence [nspid]QsoMapVariability, [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.

zmedianMag [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Median Z 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.

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

zmfID [nspid]ZYJHKmergeLog WSA NonSurvey the UID of the relevant multiframe bigint 8 ID_FRAME

zminCadence [nspid]QsoMapVariability, [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.

zMinMag [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Minimum magnitude in Z 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.

zmjExt [nspid]Source WSA NonSurvey Extended source colour Z-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.

zmjExtErr [nspid]Source WSA NonSurvey Error on extended source colour Z-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.

zmjPnt [nspid]Source WSA NonSurvey Point source colour Z-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.

zmjPntErr [nspid]Source WSA NonSurvey Error on point source colour Z-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.

zmyExt [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Extended source colour Z-Y (using aperMag3) real 4 mag -0.9999995e9 PHOT_COLOR

zmyExt [nspid]Source WSA NonSurvey Extended source colour Z-Y (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.

zmyExtErr [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Error on extended source colour Z-Y real 4 mag -0.9999995e9 ERROR

zmyExtErr [nspid]Source WSA NonSurvey Error on extended source colour Z-Y 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.

zmyPnt [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Point source colour Z-Y (using aperMag3) real 4 mag -0.9999995e9 PHOT_COLOR

zmyPnt [nspid]Source, [nspid]SynopticSource WSA NonSurvey Point source colour Z-Y (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.

zmyPntErr [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Error on point source colour Z-Y real 4 mag -0.9999995e9 ERROR

zmyPntErr [nspid]Source, [nspid]SynopticSource WSA NonSurvey Error on point source colour Z-Y 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.

zndof [nspid]QsoMapVariability, [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.

znDofAst [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of astrometric fit in Z 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.

znDofAst [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of astrometric fit in Z band. smallint 2 -9999 stat.fit.dof;stat.param;em.opt.I

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.

znDofPht [nspid]QsoMapVarFrameSetInfo WSA NonSurvey Number of degrees of freedom of photometric fit in Z band. smallint 2 -9999 stat.fit.dof;stat.param;em.opt.I

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.

znDofPht [nspid]VarFrameSetInfo WSA NonSurvey Number of degrees of freedom of photometric fit in Z 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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z 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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u08a15Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u09bh50Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u09bk2Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u10ah51Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u10bk1Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u10bk2Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u11ak3Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u11bk1Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u11bk2Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u11bk3Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u11bk4Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u11bk4bDetection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u12ak1Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u12ak2Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z 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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u12ak5Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u14bua06Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u14bua17Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u15bua19Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u16aua18Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u17auo01Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u17buo01Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u18ah02aDetection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u18ah02bDetection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u19ancu04Detection.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.

znFlaggedObs [nspid]Variability WSA NonSurvey Number of detections in Z band flagged as potentially spurious by u19bncu03Detection.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.

znGoodObs [nspid]Variability WSA NonSurvey Number of good detections in Z 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.

zNgt3sig [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Number of good detections in Z-band that are more than 3 sigma deviations (zAperMagN < (zMeanMag-3*zMagRms) 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.

zNgt3sig [nspid]Variability WSA NonSurvey Number of good detections in Z-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.

znMissingObs [nspid]Variability WSA NonSurvey Number of Z 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.

znNegFlagObs [nspid]QsoMapVariability WSA NonSurvey Number of flagged negative measurements in Z band by wserv1000MapRemeasurement.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.

znNegObs [nspid]QsoMapVariability WSA NonSurvey Number of unflagged negative measurements Z 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.

znPosFlagObs [nspid]QsoMapVariability WSA NonSurvey Number of flagged positive measurements in Z band by wserv1000MapRemeasurement.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.

znPosObs [nspid]QsoMapVariability WSA NonSurvey Number of unflagged positive measurements in Z 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.

zone [nspid]ExternalSurveyTable WSA NonSurvey default (0) or special (n) zone smallint 2 obs.field

zPA [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey ellipse fit celestial orientation in Z real 4 Degrees -0.9999995e9 POS_POS-ANG

zPetroMag [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Extended source Z mag (Petrosian) real 4 mag -0.9999995e9 PHOT_MAG

zPetroMagErr [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in extended source Z mag (Petrosian) real 4 mag -0.9999995e9 ERROR

zppErrBits [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey additional WFAU post-processing error bits in Z int 4 0 CODE_MISC

zppErrBits [nspid]Source, [nspid]SynopticSource WSA NonSurvey additional WFAU post-processing error bits in Z 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.

zprobVar [nspid]QsoMapVariability, [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.

zPsfMag [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Point source profile-fitted Z mag real 4 mag -0.9999995e9 PHOT_MAG

zPsfMagErr [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in point source profile-fitted Z mag real 4 mag -0.9999995e9 ERROR

zpSystem [nspid]ExternalProduct WSA NonSurvey System of zeropoint (Vega/AB) varchar 16 'NONE'

zpSystem [nspid]RequiredMosaicTopLevel WSA NonSurvey System of zeropoint (Vega/AB) varchar 8 'NONE'

zSeqNum [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]SynopticSource, [nspid]ZYJHKsource WSA NonSurvey the running number of the Z detection int 4 -99999999 ID_NUMBER

zSerMag2D [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Extended source Z mag (profile-fitted) real 4 mag -0.9999995e9 PHOT_MAG

zSerMag2DErr [nspid]GcsPointSource, [nspid]PointSource, [nspid]Source, [nspid]ZYJHKsource WSA NonSurvey Error in extended source Z mag (profile-fitted) real 4 mag -0.9999995e9 ERROR

zskewness [nspid]QsoMapVariability, [nspid]Variability WSA NonSurvey Skewness in Z 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.

ztotalPeriod [nspid]QsoMapVariability, [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.

zVarClass [nspid]QsoMapVariability, [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.

zXi [nspid]GcsPointSource, [nspid]PointSource, [nspid]ZYJHKsource WSA NonSurvey Offset of Z detection from master position (+east/-west) real 4 arcsec -0.9999995e9 POS_EQ_RA_OFF

zXi [nspid]Source, [nspid]SynopticSource WSA NonSurvey Offset of Z 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.

zyiWS [nspid]Variability WSA NonSurvey Welch-Stetson statistic between Z and Y. This assumes colour does not vary much and helps remove variation due to a few poor detections real 4 -0.9999995e9

The Welch-Stetson 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.

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

wsa-support@roe.ac.uk
17/01/2022