WSA Browser

Glossary of WSA attributes

This Glossary alphabetically lists all attributes used in the UKIDSSDR11 database(s) held in the WSA. If you would like to have more information about the schema tables please use the UKIDSSDR11 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

P

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

p1 catwise_2020, catwise_prelim WISE P vector component 1 real 4 arcsec

p1 cepheid, rrlyrae GAIADR1 Period corresponding to the maximum peak in the periodogram of G band time series float 8 days time.period

p1_error cepheid, rrlyrae GAIADR1 Uncertainty on the period corresponding to the maximum peak in the periodogram of G band time series float 8 days stat.error;time.period

p2 catwise_2020, catwise_prelim WISE P vector component 2 real 4 arcsec

PA nvssSource NVSS [-90, 90] Position angle of fitted major axis real 4 degress POS_POS-ANG

pa UKIDSSDetection WSA ellipse fit orientation to x axis real 4 degrees POS_POS-ANG

pa calDetection WSACalib ellipse fit orientation to x axis {catalogue TType keyword: Position_angle}
Angle of ellipse major axis wrt x axis. real 4 degrees POS_POS-ANG

pa dxsDetection, gcsDetection, gpsDetection, lasDetection WSA ellipse fit orientation to x axis {catalogue TType keyword: Position_angle}
Angle of ellipse major axis wrt x axis. real 4 degrees POS_POS-ANG

pa first08Jul16Source, firstSource, firstSource12Feb16 FIRST position angle (east of north) derived from the elliptical Gaussian model for the source real 4 degrees POS_POS-ANG

pa lasMapRemeasAver WSA Averaged ellipse fit orientation to x axis
Angle of ellipse major axis wrt x axis counterclockwise. real 4 degrees pos.posAng

pa lasMapRemeasurement WSA ellipse fit orientation to x axis {catalogue TType keyword: Position_angle}
Angle of ellipse major axis wrt x axis counterclockwise. real 4 degrees pos.posAng

pa ptsDetection WSATransit ellipse fit orientation to x axis {catalogue TType keyword: Position_angle}
Angle of ellipse major axis wrt x axis. real 4 degrees POS_POS-ANG

pa udsDetection WSA ellipse fit orientation to x axis {catalogue TType keyword: Position_angle}
Angle of ellipse major axis wrt x axis counterclockwise. real 4 degrees POS_POS-ANG

pa uhsDetection, uhsDetectionAll WSAUHS ellipse fit orientation to x axis {catalogue TType keyword: Position_angle}
Angle of ellipse major axis wrt x axis. real 4 degrees POS_POS-ANG

pa_2mass allwise_sc WISE Position angle (degrees E of N) of the vector from the WISE source to the associated 2MASS PSC source. This column is "null" if there is no associated 2MASS PSC source. float 8 deg

pa_2mass wise_allskysc WISE Position angle (degrees E of N) of the vector from the WISE source to the associated 2MASS PSC source, default if there is no associated 2MASS PSC source. real 4 degrees -0.9999995e9

pa_2mass wise_prelimsc WISE Position angle (degrees E of N) of the vector from the WISE source to the associated 2MASS PSC source, default if there is no associated 2MASS PSC source real 4 degrees -0.9999995e9

pairingCriterion Programme WSA The pairing criterion for associating detections into merged sources real 4 Degrees ??

pairingCriterion Programme WSACalib The pairing criterion for associating detections into merged sources real 4 Degrees ??

pairingCriterion Programme WSATransit The pairing criterion for associating detections into merged sources real 4 Degrees ??

pairingCriterion Programme WSAUHS The pairing criterion for associating detections into merged sources real 4 Degrees ??

par_pm catwise_2020, catwise_prelim WISE parallax from PM desc-asce elon real 4 arcsec

par_pm is computed from the motion-solution positions, which are translated by WPHotpmc to the standard epoch (MJD0), so except for estimation errors, par_pm is the parallax; par_pm will be null unless km = 3.

par_pmSig catwise_2020, catwise_prelim WISE one-sigma uncertainty in par_pm real 4 arcsec

par_sigma catwise_2020, catwise_prelim WISE one-sigma uncertainty in par_stat real 4 arcsec

par_stat catwise_2020, catwise_prelim WISE parallax estimate from stationary solution real 4 arcsec

The par_stat column is computed by using the motion estimate to move the ascending stationary-solution position from the ascending effective observation epoch to that of the descending solution, then dividing the ecliptic longitude difference by 2; par_stat will be null unless ka = 3 AND km > 0 AND all W?mJDmin/max/mean values are non-null in both ascending and descending mdex files.

parallax calVariability WSACalib Parallax of star real 4 mas -0.9999995e9

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.

parallax dxsVariability, gcsVariability, gpsVariability, lasVariability, udsVariability WSA Parallax of star real 4 mas -0.9999995e9

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.

parallax gaia_source GAIADR2 Parallax float 8 milliarcsec pos.parallax

parallax gaia_source GAIAEDR3 Parallax float 8 milliarcsec pos.parallax

parallax gaia_source, tgas_source GAIADR1 Parallax float 8 milliarcsec pos.parallax

parallax uhsVariability WSAUHS Parallax of star real 4 mas -0.9999995e9

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.

parallax_error gaia_source GAIADR2 Standard error of parallax float 8 milliarcsec stat.error;pos.parallax

parallax_error gaia_source GAIAEDR3 Standard error of parallax float 8 milliarcsec stat.error;pos.parallax

parallax_error gaia_source, tgas_source GAIADR1 Standard error of parallax float 8 milliarcsec stat.error;pos.parallax

parallax_over_error gaia_source GAIADR2 Parallax divided by standard error real 4 arith.ratio

parallax_over_error gaia_source GAIAEDR3 Parallax divided by standard error real 4 arith.ratio

parallax_pmdec_corr gaia_source GAIADR2 Correlation between parallax and proper motion in Declination real 4 stat.correlation;pos.parallax;pos.pm;pos.eq.dec

parallax_pmdec_corr gaia_source GAIAEDR3 Correlation between parallax and proper motion in Declination real 4 stat.correlation;pos.parallax;pos.pm;pos.eq.dec

parallax_pmdec_corr gaia_source, tgas_source GAIADR1 Correlation between parallax and proper motion in Declination real 4 stat.correlation

parallax_pmra_corr gaia_source GAIADR2 Correlation between parallax and proper motion in Right Ascension real 4 stat.correlation;pos.parallax;pos.pm;pos.eq.ra

parallax_pmra_corr gaia_source GAIAEDR3 Correlation between parallax and proper motion in Right Ascension real 4 stat.correlation;pos.parallax;pos.pm;pos.eq.ra

parallax_pmra_corr gaia_source, tgas_source GAIADR1 Correlation between parallax and proper motion in Right Ascension real 4 stat.correlation

parallax_pseudocolour_corr gaia_source GAIAEDR3 Correlation between parallax and pseudocolour real 4 stat.correlation;em.wavenumber;pos.parallax

paramTemplate RequiredMosaicTopLevel WSAUHS Template file for SWARP parameters varchar 32

pcSysID MultiframeDetector WSA PC system identifier {image extension keyword: PCSYSID} varchar 32 NONE ??

pcSysID MultiframeDetector WSACalib PC system identifier {image extension keyword: PCSYSID} varchar 32 NONE ??

pcSysID MultiframeDetector WSATransit PC system identifier {image extension keyword: PCSYSID} varchar 32 NONE ??

pcSysID MultiframeDetector WSAUHS PC system identifier {image extension keyword: PCSYSID} varchar 32 NONE ??

peak_to_peak_g cepheid, rrlyrae GAIADR1 Peak-to-peak amplitude of the G band light curve float 8 mag src.var.amplitude;em.opt

peak_to_peak_g_error cepheid, rrlyrae GAIADR1 Uncertainty on peak-to-peak amplitude of the G band light curve float 8 mag stat.error;src.var.amplitude;em.opt

petroFlux UKIDSSDetection WSA flux within circular aperture to k × r_p ; k = 2 real 4 ADU PHOT_INTENSITY_ADU

petroFlux calDetection WSACalib flux within circular aperture to k × r_p ; k = 2 {catalogue TType keyword: Petr_flux} real 4 ADU PHOT_INTENSITY_ADU

petroFlux dxsDetection, gcsDetection, gpsDetection, lasDetection WSA flux within circular aperture to k × r_p ; k = 2 {catalogue TType keyword: Petr_flux} real 4 ADU PHOT_INTENSITY_ADU

petroFlux lasMapRemeasurement WSA flux within Petrosian radius circular aperture (SE: FLUX_PETRO; CASU: default) {catalogue TType keyword: Petr_flux} real 4 ADU phot.count

petroFlux ptsDetection WSATransit flux within circular aperture to k × r_p ; k = 2 {catalogue TType keyword: Petr_flux} real 4 ADU PHOT_INTENSITY_ADU

petroFlux udsDetection WSA flux within Petrosian radius circular aperture (SE: FLUX_PETRO) {catalogue TType keyword: Petr_flux} real 4 ADU PHOT_INTENSITY_ADU

petroFlux uhsDetection, uhsDetectionAll WSAUHS flux within circular aperture to k × r_p ; k = 2 {catalogue TType keyword: Petr_flux} real 4 ADU PHOT_INTENSITY_ADU

petroFluxErr UKIDSSDetection WSA error on Petrosian flux real 4 ADU ERROR

petroFluxErr calDetection WSACalib error on Petrosian flux {catalogue TType keyword: Petr_flux_err} real 4 ADU ERROR

petroFluxErr dxsDetection, gcsDetection, gpsDetection, lasDetection WSA error on Petrosian flux {catalogue TType keyword: Petr_flux_err} real 4 ADU ERROR

petroFluxErr lasMapRemeasurement WSA error on Petrosian flux (SE: FLUXERR_PETRO; CASU: default) {catalogue TType keyword: Petr_flux_err} real 4 ADU stat.error

petroFluxErr ptsDetection WSATransit error on Petrosian flux {catalogue TType keyword: Petr_flux_err} real 4 ADU ERROR

petroFluxErr udsDetection WSA error on Petrosian flux (SE: FLUXERR_PETRO) {catalogue TType keyword: Petr_flux_err} real 4 ADU ERROR

petroFluxErr uhsDetection, uhsDetectionAll WSAUHS error on Petrosian flux {catalogue TType keyword: Petr_flux_err} real 4 ADU ERROR

petroJky lasMapRemeasurement WSA Calibrated Petrosian flux within aperture r_p (CASU: default) real 4 jansky phot.mag

petroJkyErr lasMapRemeasurement WSA error on calibrated Petrosian flux (CASU: default) real 4 jansky stat.error

petroLup lasMapRemeasurement WSA Calibrated Petrosian luptitude within aperture r_p (CASU: default) real 4 lup phot.mag

petroLupErr lasMapRemeasurement WSA error on calibrated Petrosian luptitude (CASU: default) real 4 lup stat.error

petroMag dxsDetection, gcsDetection, gpsDetection, lasDetection, UKIDSSDetection, udsDetection WSA Calibrated Petrosian magnitude within circular aperture r_p real 4 mag PHOT_INT-MAG

petroMag calDetection WSACalib Calibrated Petrosian magnitude within circular aperture r_p real 4 mag PHOT_INT-MAG

petroMag lasMapRemeasurement WSA Calibrated Petrosian magnitude within aperture r_p (CASU: default) real 4 mag phot.mag

petroMag ptsDetection WSATransit Calibrated Petrosian magnitude within circular aperture r_p real 4 mag PHOT_INT-MAG

petroMag uhsDetection, uhsDetectionAll WSAUHS Calibrated Petrosian magnitude within circular aperture r_p real 4 mag PHOT_INT-MAG

petroMagErr dxsDetection, gcsDetection, gpsDetection, lasDetection, UKIDSSDetection, udsDetection WSA error on calibrated Petrosian magnitude real 4 mag ERROR

petroMagErr calDetection WSACalib error on calibrated Petrosian magnitude real 4 mag ERROR

petroMagErr lasMapRemeasurement WSA error on calibrated Petrosian magnitude (CASU: default) real 4 mag stat.error

petroMagErr ptsDetection WSATransit error on calibrated Petrosian magnitude real 4 mag ERROR

petroMagErr uhsDetection, uhsDetectionAll WSAUHS error on calibrated Petrosian magnitude real 4 mag ERROR

petroRad UKIDSSDetection WSA r_p as defined in Yasuda et al. 2001 AJ 112 1104 real 4 pixels EXTENSION_RAD

petroRad calDetection WSACalib r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius} real 4 pixels EXTENSION_RAD

petroRad dxsDetection, gcsDetection, gpsDetection, lasDetection WSA r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius} real 4 pixels EXTENSION_RAD

petroRad lasMapRemeasurement WSA Petrosian radius (SE: PETRO_RADIUS*A_IMAGE; CASU: default) {catalogue TType keyword: Petr_radius} real 4 pixels phys.angSize

Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels.

petroRad ptsDetection WSATransit r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius} real 4 pixels EXTENSION_RAD

petroRad udsDetection WSA Petrosian radius (SE: PETRO_RADIUS*A_IMAGE) {catalogue TType keyword: Petr_radius} real 4 pixels EXTENSION_RAD

Since <FLUX>_RADIUS is expressed in multiples of the major axis, <FLUX>_RADIUS is multiplied by A_IMAGE to convert to pixels.

petroRad uhsDetection, uhsDetectionAll WSAUHS r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius} real 4 pixels EXTENSION_RAD

PF_DEC mgcBrightSpec MGC PFr object declination in deg (J2000) float 8

PF_JMK mgcBrightSpec MGC PFr J-K colour from 2MASS real 4

PF_K mgcBrightSpec MGC PFr K magnitude from 2MASS real 4

PF_NAME mgcBrightSpec MGC PFr object name varchar 8

PF_R mgcBrightSpec MGC PFr R magnitude from USNO real 4

PF_RA mgcBrightSpec MGC PFr object right ascension in deg (J2000) float 8

PF_Z mgcBrightSpec MGC PFr redshift real 4

PF_ZQUAL mgcBrightSpec MGC PFr redshift quality tinyint 1

pFlag rosat_bsc, rosat_fsc ROSAT possible problem with position determination varchar 1 CODE_MISC

pflag tycho2 GAIADR1 Mean position flag varchar 1 meta.code

pGalaxy calSource, calSynopticSource WSACalib Probability that the source is a galaxy real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pGalaxy dxsJKsource, gcsPointSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, lasExtendedSource, lasPointSource, lasYJHKsource, reliableDxsSource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource, reliableUdsSource WSA Probability that the source is a galaxy real 4 STAT_PROP

pGalaxy dxsSource, gcsSource, gpsSource, lasSource, udsSource WSA Probability that the source is a galaxy real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pGalaxy lasYselJSourceRemeasurement WSA Probability that the source is a galaxy real 4 stat.probability

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pGalaxy uhsSource, uhsSourceAll WSAUHS Probability that the source is a galaxy real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

ph_qual allwise_sc WISE Photometric quality flag. Four character flag, one character per band [W1/W2/W3/W4], that provides a shorthand summary of the quality of the profile-fit photometry measurement in each band, as derived from the measurement signal-to-noise ratio. varchar 4

A - Source is detected in this band with a flux signal-to-noise ratio w?snr>10.

B - Source is detected in this band with a flux signal-to-noise ratio 3<w?snr<10.

C - Source is detected in this band with a flux signal-to-noise ratio 2<w?snr<3.

U - Upper limit on magnitude. Source measurement has w?snr<2. The profile-fit magnitude w?mpro is a 95% confidence upper limit.

X - A profile-fit measurement was not possible at this location in this band. The value of w?mpro and w?sigmpro will be "null" in this band.

Z - A profile-fit source flux measurement was made at this location, but the flux uncertainty could not be measured. The value of w?sigmpro will be "null" in this band. The value of w?mpro will be "null" if the measured flux, w?flux, is negative, but will not be "null" if the flux is positive. If a non-null magnitude is present, it corresponds to the true flux, and not the 95% confidence upper limit. This occurs for a small number of sources found in a narrow range of ecliptic longitude which were covered by a large number of saturated pixels from 3-Band Cryo single-exposures.

ph_qual twomass_psc 2MASS Photometric quality flag. varchar 3 CODE_QUALITY

ph_qual twomass_sixx2_psc 2MASS flag indicating photometric quality of source varchar 3

ph_qual wise_allskysc WISE Photometric quality flag.
Four character flag, one character per band [W1/W2/W3/W4], that provides a shorthand summary of the quality of the profile-fit photometry measurement in each band, as derived from the measurement signal-to-noise ratio. char 4

ph_qual wise_prelimsc WISE Photometric quality flag
Four character flag, one character per band [W1/W2/W3/W4], that provides a shorthand summary of the quality of the profile-fit photometry measurement in each band, as derived from the measurement signal-to-noise ratio char 4

phaRange rosat_bsc, rosat_fsc ROSAT PHA range with highest detection likelihood varchar 1 CODE_MISC

pHeight UKIDSSDetection WSA Highest pixel value above sky real 4 ADU PHOT_COUNTS_MISC

pHeight calDetection WSACalib Highest pixel value above sky {catalogue TType keyword: Peak_height}
In counts relative to local value of sky - also zeroth order aperture flux. real 4 ADU PHOT_COUNTS_MISC

pHeight dxsDetection, gcsDetection, gpsDetection, lasDetection WSA Highest pixel value above sky {catalogue TType keyword: Peak_height}
In counts relative to local value of sky - also zeroth order aperture flux. real 4 ADU PHOT_COUNTS_MISC

pHeight lasMapRemeasurement WSA Highest pixel value above sky (SE: FLUX_MAX) {catalogue TType keyword: Peak_height}
In counts relative to local value of sky - also zeroth order aperture flux. real 4 ADU phot.count

pHeight ptsDetection WSATransit Highest pixel value above sky {catalogue TType keyword: Peak_height}
In counts relative to local value of sky - also zeroth order aperture flux. real 4 ADU PHOT_COUNTS_MISC

pHeight udsDetection WSA Highest pixel value above sky (SE: FLUX_MAX) {catalogue TType keyword: Peak_height}
In counts relative to local value of sky - also zeroth order aperture flux. real 4 ADU PHOT_COUNTS_MISC

pHeight uhsDetection, uhsDetectionAll WSAUHS Highest pixel value above sky {catalogue TType keyword: Peak_height}
In counts relative to local value of sky - also zeroth order aperture flux. real 4 ADU PHOT_COUNTS_MISC

pHeightErr UKIDSSDetection WSA Error in peak height real 4 ADU ERROR

pHeightErr calDetection WSACalib Error in peak height {catalogue TType keyword: Peak_height_err} real 4 ADU ERROR

pHeightErr dxsDetection, gcsDetection, gpsDetection, lasDetection WSA Error in peak height {catalogue TType keyword: Peak_height_err} real 4 ADU ERROR

pHeightErr lasMapRemeasurement WSA Error in peak height {catalogue TType keyword: Peak_height_err}
FLUX_MAX*FLUXERR_APER1 / FLUX_APER1 real 4 ADU stat.error

pHeightErr ptsDetection WSATransit Error in peak height {catalogue TType keyword: Peak_height_err} real 4 ADU ERROR

pHeightErr udsDetection WSA Error in peak height {catalogue TType keyword: Peak_height_err}
FLUX_MAX*FLUXERR_APER1 / FLUX_APER1 real 4 ADU ERROR

pHeightErr uhsDetection, uhsDetectionAll WSAUHS Error in peak height {catalogue TType keyword: Peak_height_err} real 4 ADU ERROR

phi21_g cepheid, rrlyrae GAIADR1 Fourier decomposition parameter phi21G: phi2 - 2*phi1 (for G band) float 8 stat.Fourier

phi21_g_error cepheid, rrlyrae GAIADR1 Uncertainty on Fourier decomposition parameter phi21G float 8 stat.error

phi_opt twomass_psc 2MASS Position angle on the sky of the vector from the the associated optical source to the TWOMASS source position, in degrees East of North. smallint 2 degrees POS_POS-ANG

phot_bp_mean_flux gaia_source GAIADR2 Integrated BP mean flux float 8 electrons/s phot.flux;stat.mean

phot_bp_mean_flux gaia_source GAIAEDR3 Integrated BP mean flux float 8 electrons/s phot.flux;stat.mean

phot_bp_mean_flux_error gaia_source GAIADR2 Standard error on the integrated BP mean flux float 8 electrons/s stat.error;phot.flux;stat.mean

phot_bp_mean_flux_error gaia_source GAIAEDR3 Standard error on the integrated BP mean flux real 4 electrons/s stat.error;phot.flux;stat.mean

phot_bp_mean_flux_over_error gaia_source GAIADR2 Integrated mean BP flux divided by its standard error real 4 arith.ratio

phot_bp_mean_flux_over_error gaia_source GAIAEDR3 Integrated mean BP flux divided by its standard error real 4 arith.ratio

phot_bp_mean_mag gaia_source GAIADR2 Integrated BP mean magnitude real 4 mag phot.mag;stat.mean

phot_bp_mean_mag gaia_source GAIAEDR3 Integrated BP mean magnitude real 4 mag phot.mag;stat.mean

phot_bp_n_blended_transits gaia_source GAIAEDR3 Number of BP blended transits smallint 2 meta.number

phot_bp_n_contaminated_transits gaia_source GAIAEDR3 Number of BP contaminated transits smallint 2 meta.number

phot_bp_n_obs gaia_source GAIADR2 Number of observations contributing to BP photometry int 4 meta.number

phot_bp_n_obs gaia_source GAIAEDR3 Number of observations contributing to BP photometry smallint 2 meta.number

phot_bp_rp_excess_factor gaia_source GAIADR2 Combined BP and RP excess factor real 4

phot_bp_rp_excess_factor gaia_source GAIAEDR3 Combined BP and RP excess factor real 4 arith.factor;phot.flux;em.opt

phot_g_mean_flux gaia_source GAIADR2 G-band mean flux float 8 electrons/s phot.flux;stat.mean;em.opt

phot_g_mean_flux gaia_source GAIAEDR3 G-band mean flux float 8 electrons/s phot.flux;stat.mean;em.opt

phot_g_mean_flux gaia_source, tgas_source GAIADR1 G-band mean flux float 8 electrons/s phot.flux;stat.mean;em.opt

phot_g_mean_flux_error gaia_source GAIADR2 Error on G-band mean flux float 8 electrons/s stat.error;phot.flux;stat.mean;em.opt

phot_g_mean_flux_error gaia_source GAIAEDR3 Error on G-band mean flux real 4 electrons/s stat.error;phot.flux;stat.mean;em.opt

phot_g_mean_flux_error gaia_source, tgas_source GAIADR1 Error on G-band mean flux float 8 electrons/s stat.error;phot.flux;stat.mean;em.opt

phot_g_mean_flux_over_error gaia_source GAIADR2 G-band mean flux divided by its standard error float 8 arith.ratio

phot_g_mean_flux_over_error gaia_source GAIAEDR3 G-band mean flux divided by its standard error real 4 arith.ratio

phot_g_mean_mag aux_qso_icrf2_match, gaia_source, tgas_source GAIADR1 G-band mean magnitude float 8 mag phot.mag;stat.mean;em.opt

phot_g_mean_mag gaia_source GAIADR2 G-band mean magnitude real 4 mag phot.mag;stat.mean;em.opt

phot_g_mean_mag gaia_source GAIAEDR3 G-band mean magnitude real 4 mag phot.mag;stat.mean;em.opt

phot_g_n_obs gaia_source GAIADR2 Number of observations contributing to G band photometry int 4 meta.number

phot_g_n_obs gaia_source GAIAEDR3 Number of observations contributing to G band photometry smallint 2 meta.number

phot_g_n_obs gaia_source, tgas_source GAIADR1 Number of observations contributing to G band photometry int 4 meta.number

phot_proc_mode gaia_source GAIADR2 Photometry processing mode tinyint 1 meta.code

phot_proc_mode gaia_source GAIAEDR3 Photometry processing mode tinyint 1 meta.code

phot_rp_mean_flux gaia_source GAIADR2 Integrated RP mean flux float 8 electrons/s phot.flux;stat.mean

phot_rp_mean_flux gaia_source GAIAEDR3 Integrated RP mean flux float 8 electrons/s phot.flux;stat.mean

phot_rp_mean_flux_error gaia_source GAIADR2 Standard error on the integrated RP mean flux float 8 electrons/s stat.error;phot.flux;stat.mean

phot_rp_mean_flux_error gaia_source GAIAEDR3 Standard error on the integrated RP mean flux real 4 electrons/s stat.error;phot.flux;stat.mean

phot_rp_mean_flux_over_error gaia_source GAIADR2 Integrated mean RP flux divided by its standard error real 4 arith.ratio

phot_rp_mean_flux_over_error gaia_source GAIAEDR3 Integrated mean RP flux divided by its standard error real 4 arith.ratio

phot_rp_mean_mag gaia_source GAIADR2 Integrated RP mean magnitude real 4 mag phot.mag;stat.mean

phot_rp_mean_mag gaia_source GAIAEDR3 Integrated RP mean magnitude real 4 mag phot.mag;stat.mean

phot_rp_n_blended_transits gaia_source GAIAEDR3 Number of RP blended transits smallint 2 meta.number

phot_rp_n_contaminated_transits gaia_source GAIAEDR3 Number of RP contaminated transits smallint 2 meta.number

phot_rp_n_obs gaia_source GAIADR2 Number of observations contributing to RP photometry int 4 meta.number

phot_rp_n_obs gaia_source GAIAEDR3 Number of observations contributing to RP photometry smallint 2 meta.number

phot_variable_flag gaia_source GAIADR2 Photometric variability flag char 16 meta.code;src.var

phot_variable_flag gaia_source, tgas_source GAIADR1 Photometric variability flag varchar 16 meta.code;src.var

phot_variable_fundam_freq1 variable_summary GAIADR1 Fundamental frequency 1 float 8 /days src.var.pulse

photZPCat MultiframeDetector WSA Photometric zero point for default extinction for the catalogue data {catalogue extension keyword: MAGZPT} real 4 mags -0.9999995e9 ??

Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use
ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct
You can then make use of any of the assorted flux estimators to produce magnitudes via
Mag = ZP - 2.5*log₁₀(flux/exptime) - aperCor - skyCorr
Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction.

photZPCat MultiframeDetector WSACalib Photometric zero point for default extinction for the catalogue data {catalogue extension keyword: MAGZPT} real 4 mags -0.9999995e9 ??

Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use
ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct
You can then make use of any of the assorted flux estimators to produce magnitudes via
Mag = ZP - 2.5*log₁₀(flux/exptime) - aperCor - skyCorr
Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction.

photZPCat MultiframeDetector WSATransit Photometric zero point for default extinction for the catalogue data {catalogue extension keyword: MAGZPT} real 4 mags -0.9999995e9 ??

Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use
ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct
You can then make use of any of the assorted flux estimators to produce magnitudes via
Mag = ZP - 2.5*log₁₀(flux/exptime) - aperCor - skyCorr
Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction.

photZPCat MultiframeDetector WSAUHS Photometric zero point for default extinction for the catalogue data {catalogue extension keyword: MAGZPT} real 4 mags -0.9999995e9 ??

Derived detector zero-point in the sense of what magnitude object gives a total (corrected) flux of 1 count/s. These ZPs are appropriate for generating magnitudes in the natural detector+filter system based on Vega, see CASU reports for more details on colour equations etc. The ZPs have been derived from a robust average of all photometric standards observed on any particular set of frames, corrected for airmass but assuming the default extinction values listed later. For other airmass or other values of the extinction use
ZP → ZP - [sec(z)-1]×extinct + extinct default - extinct
You can then make use of any of the assorted flux estimators to produce magnitudes via
Mag = ZP - 2.5*log₁₀(flux/exptime) - aperCor - skyCorr
Note that for the so-called total and isophotal flux options it is not possible to have a single-valued aperture correction.

photZPCat PreviousMFDZP WSA Photometric zeropoint for default extinction in catalogue header real 4 mag -0.9999995e9

photZPCat PreviousMFDZP WSACalib Photometric zeropoint for default extinction in catalogue header real 4 mag -0.9999995e9

photZPCat PreviousMFDZP WSAUHS Photometric zeropoint for default extinction in catalogue header real 4 mag -0.9999995e9

photZPErrCat MultiframeDetector WSA Photometric zero point error for the catalogue data {catalogue extension keyword: MAGZRR}
[Currently set to -1 for WFCAM data.] real 4 mags -0.9999995e9 ??

Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse.

photZPErrCat MultiframeDetector WSACalib Photometric zero point error for the catalogue data {catalogue extension keyword: MAGZRR}
[Currently set to -1 for WFCAM data.] real 4 mags -0.9999995e9 ??

Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse.

photZPErrCat MultiframeDetector WSATransit Photometric zero point error for the catalogue data {catalogue extension keyword: MAGZRR}
[Currently set to -1 for WFCAM data.] real 4 mags -0.9999995e9 ??

Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse.

photZPErrCat MultiframeDetector WSAUHS Photometric zero point error for the catalogue data {catalogue extension keyword: MAGZRR}
[Currently set to -1 for WFCAM data.] real 4 mags -0.9999995e9 ??

Error in the zero point. If good photometric night this error will be at the level of a few percent. Values of 0.05 and above indicate correspondingly non-photometric night and worse.

photZPErrCat PreviousMFDZP WSA Photometric zeropoint error in catalogue header real 4 mag -0.9999995e9

photZPErrCat PreviousMFDZP WSACalib Photometric zeropoint error in catalogue header real 4 mag -0.9999995e9

photZPErrCat PreviousMFDZP WSAUHS Photometric zeropoint error in catalogue header real 4 mag -0.9999995e9

pixelScale MultiframeDetector WSA Warning - Original detector pixel size, the actual angular pixel size is written to xPixSize and yPixSize in the CurrentAstrometry table {image extension keyword: PIXLSIZE} real 4 arcsec per pixel -0.9999995e9 phys.angSize;instr.pixel

pixelScale MultiframeDetector WSACalib Warning - Original detector pixel size, the actual angular pixel size is written to xPixSize and yPixSize in the CurrentAstrometry table {image extension keyword: PIXLSIZE} real 4 arcsec per pixel -0.9999995e9 phys.angSize;instr.pixel

pixelScale MultiframeDetector WSATransit Warning - Original detector pixel size, the actual angular pixel size is written to xPixSize and yPixSize in the CurrentAstrometry table {image extension keyword: PIXLSIZE} real 4 arcsec per pixel -0.9999995e9 phys.angSize;instr.pixel

pixelScale MultiframeDetector WSAUHS Warning - Original detector pixel size, the actual angular pixel size is written to xPixSize and yPixSize in the CurrentAstrometry table {image extension keyword: PIXLSIZE} real 4 arcsec per pixel -0.9999995e9 phys.angSize;instr.pixel

pixelSize RequiredMosaic WSA The final pixel size of the mosaic real 4 arcsec -0.9999995e9 ??

pixelSize RequiredMosaic WSACalib The final pixel size of the mosaic real 4 arcsec -0.9999995e9 ??

pixelSize RequiredMosaic WSATransit The final pixel size of the mosaic real 4 arcsec -0.9999995e9 ??

pixelSize RequiredMosaic, RequiredMosaicTopLevel WSAUHS The final pixel size of the mosaic real 4 arcsec -0.9999995e9 ??

pltScale Detection PS1DR2 Local plate scale at this location. real 4 arcsec/pixel -999

plx hipparcos_new_reduction GAIADR1 Parallax float 8 milliarcseconds pos.parallax

pm gaia_source GAIAEDR3 Total proper motion real 4 milliarcsec/year pos.pm;pos.eq

pm_de hipparcos_new_reduction GAIADR1 Proper motion in Declination float 8 milliarcseconds/year pos.eq.dec;pos.pm

pm_de tycho2 GAIADR1 Proper motion in Dec real 4 milliarcsec/year pos.eq.dec;pos.pm

pm_dec igsl_source GAIADR1 Proper motion in Dec at catalogue epoch real 4 milliarcsec/year pos.pm;pos.eq.dec

pm_dec_error igsl_source GAIADR1 Error in proper motion in Dec real 4 milliarcsec/year stat.error;pos.pm;pos.eq.dec

pm_ra hipparcos_new_reduction GAIADR1 Proper motion in Right Ascension float 8 milliarcseconds/year pos.eq.ra;pos.pm

pm_ra igsl_source GAIADR1 Proper motion in RA at catalogue epoch real 4 milliarcsec/year pos.pm;pos.eq.ra

pm_ra tycho2 GAIADR1 Proper motion in RA*cos(Dec) real 4 milliarcsec/year pos.eq.ra;pos.pm

pm_ra_error igsl_source GAIADR1 Error in proper motion in RA real 4 milliarcsec/year stat.error;pos.pm;pos.eq.ra

pmcode allwise_sc WISE This is a five character string that encodes information about factors that impact the accuracy of the motion estimation. These include the original blend count, whether a blend-swap took place, and the distance in hundredths of an arcsecond between the non-motion position and the motion mean-observation-epoch position. This column is null if a motion solution was not attempted or a valid solution was not found. varchar 5

The format is NQDDD where N is the original blend count, Q is either "Y" or "N" for "yes" or "no" a blend-swap occurred (i.e., the original primary component was not the final primary component), and DDD is the radial distance between the non-motion and motion at mean-observation epoch positions in units of 0.01 arcsec, clipped at 999 (almost 10 arcsec).
For example, a well-behaved source that is not part of a blend and that has similar stationary and motion fit positions would have a pmcode value like "1N008". A source with a questionable motion estimate that is passively deblended (nb=2) and whose stationary-fit and motion position differ by a significant amount would have a pmcode value like "3Y234".

pmcode catwise_2020, catwise_prelim WISE quality of the PM solution varchar 5

PMDec catwise_2020, catwise_prelim WISE proper motion in dec real 4 arcsec/yr

pmDec ukirtFSstars WSA Proper motion in Dec real 4 arcsec per year 0.0

pmDec ukirtFSstars WSACalib Proper motion in Dec real 4 arcsec per year 0.0

pmDec ukirtFSstars WSAUHS Proper motion in Dec real 4 arcsec per year 0.0

pmdec allwise_sc WISE The apparent motion in declination estimated for this source. This column is null if the motion fit failed to converge or was not attempted. CAUTION: This is the total motion in declination, and not the proper motion. The apparent motion can be significantly affected by parallax for nearby objects. int 4 mas/year

pmdec gaia_source GAIADR2 Proper motion in Declination direction float 8 milliarcsec/year pos.pm;.pos.eq.dec

pmdec gaia_source GAIAEDR3 Proper motion in Declination direction float 8 milliarcsec/year pos.pm;.pos.eq.dec

pmdec gaia_source, tgas_source GAIADR1 Proper motion in Declination direction float 8 milliarcsec/year pos.pm;.pos.eq.dec

pmdec_error gaia_source GAIADR2 Error of proper motion in Declination direction float 8 milliarcsec/year stat.error;pos.pm;.pos.eq.dec

pmdec_error gaia_source GAIAEDR3 Error of proper motion in Declination direction real 4 milliarcsec/year stat.error;pos.pm;.pos.eq.dec

pmdec_error gaia_source, tgas_source GAIADR1 Error of proper motion in Declination direction float 8 milliarcsec/year stat.error;pos.pm;.pos.eq.dec

pmdec_pseudocolour_corr gaia_source GAIAEDR3 Correlation between proper motion in declination and pseudocolour real 4 stat.correlation;em.wavenumber;pos.pm;pos.eq.dec

PMRA catwise_2020, catwise_prelim WISE motion in ra real 4 arcsec/yr

pmRA ukirtFSstars WSA Proper motion in RA real 4 arcsec per year 0.0

pmRA ukirtFSstars WSACalib Proper motion in RA real 4 arcsec per year 0.0

pmRA ukirtFSstars WSAUHS Proper motion in RA real 4 arcsec per year 0.0

pmra allwise_sc WISE The apparent motion in right ascension estimated for this source. This column is null if the motion fit failed to converge or was not attempted. CAUTION: This is the total motion in right ascension, and not the proper motion. The apparent motion can be significantly affected by parallax for nearby objects. int 4 mas/year

pmra gaia_source GAIADR2 Proper motion in Right Ascension direction float 8 milliarcsec/year pos.pm;.pos.eq.ra

pmra gaia_source GAIAEDR3 Proper motion in Right Ascension direction float 8 milliarcsec/year pos.pm;.pos.eq.ra

pmra gaia_source, tgas_source GAIADR1 Proper motion in Right Ascension direction float 8 milliarcsec/year pos.pm;.pos.eq.ra

pmra_error gaia_source GAIADR2 Error of proper motion in Right Ascension direction float 8 milliarcsec/year stat.error;pos.pm;.pos.eq.ra

pmra_error gaia_source GAIAEDR3 Error of proper motion in Right Ascension direction real 4 milliarcsec/year stat.error;pos.pm;.pos.eq.ra

pmra_error gaia_source, tgas_source GAIADR1 Error of proper motion in Right Ascension direction float 8 milliarcsec/year stat.error;pos.pm;.pos.eq.ra

pmra_pmdec_corr gaia_source GAIADR2 Correlation between proper motion in Right Ascension and proper motion in Declination real 4 stat.correlation;pos.pm;pos.eq.ra;pos.pm;pos.eq.dec

pmra_pmdec_corr gaia_source GAIAEDR3 Correlation between proper motion in Right Ascension and proper motion in Declination real 4 stat.correlation;pos.pm;pos.eq.ra;pos.pm;pos.eq.dec

pmra_pmdec_corr gaia_source, tgas_source GAIADR1 Correlation between proper motion in Right Ascension and proper motion in Declination real 4 stat.correlation

pmra_pseudocolour_corr gaia_source GAIAEDR3 Correlation between proper motion in right ascension and pseudocolour real 4 stat.correlation;em.wavenumber;pos.pm;pos.eq.ra

PN_1_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 1 background map.
Made using a 12 x 12 nodes spline fit on the source-free individual-band images. real 4 counts/pixel

PN_1_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 1 Maximum likelihood real 4

PN_1_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 1 exposure map, combining the mirror vignetting, detector efficiency, bad pixels and CCD gaps.
The PSF weighted mean of the area of the subimages (radius 60 arcseconds) in the individual-band exposure maps. real 4 s

PN_1_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 1 flux real 4 erg/cm**2/s

PN_1_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 1 flux error real 4 erg/cm**2/s

PN_1_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 1 Count rates real 4 counts/s

PN_1_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 1 Count rates error real 4 counts/s

PN_1_VIG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 1 vignetting value. real 4

PN_2_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 2 background map.
Made using a 12 x 12 nodes spline fit on the source-free individual-band images. real 4 counts/pixel

PN_2_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 2 Maximum likelihood real 4

PN_2_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 2 exposure map, combining the mirror vignetting, detector efficiency, bad pixels and CCD gaps.
The PSF weighted mean of the area of the subimages (radius 60 arcseconds) in the individual-band exposure maps. real 4 s

PN_2_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 2 flux real 4 erg/cm**2/s

PN_2_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 2 flux error real 4 erg/cm**2/s

PN_2_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 2 Count rates real 4 counts/s

PN_2_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 2 Count rates error real 4 counts/s

PN_2_VIG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 2 vignetting value. real 4

PN_3_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 3 background map.
Made using a 12 x 12 nodes spline fit on the source-free individual-band images. real 4 counts/pixel

PN_3_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 3 Maximum likelihood real 4

PN_3_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 3 exposure map, combining the mirror vignetting, detector efficiency, bad pixels and CCD gaps.
The PSF weighted mean of the area of the subimages (radius 60 arcseconds) in the individual-band exposure maps. real 4 s

PN_3_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 3 flux real 4 erg/cm**2/s

PN_3_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 3 flux error real 4 erg/cm**2/s

PN_3_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 3 Count rates real 4 counts/s

PN_3_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 3 Count rates error real 4 counts/s

PN_3_VIG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 3 vignetting value. real 4

PN_4_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 4 background map.
Made using a 12 x 12 nodes spline fit on the source-free individual-band images. real 4 counts/pixel

PN_4_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 4 Maximum likelihood real 4

PN_4_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 4 exposure map, combining the mirror vignetting, detector efficiency, bad pixels and CCD gaps.
The PSF weighted mean of the area of the subimages (radius 60 arcseconds) in the individual-band exposure maps. real 4 s

PN_4_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 4 flux real 4 erg/cm**2/s

PN_4_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 4 flux error real 4 erg/cm**2/s

PN_4_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 4 Count rates real 4 counts/s

PN_4_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 4 Count rates error real 4 counts/s

PN_4_VIG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 4 vignetting value. real 4

PN_5_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 5 background map.
Made using a 12 x 12 nodes spline fit on the source-free individual-band images. real 4 counts/pixel

PN_5_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 5 Maximum likelihood real 4

PN_5_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 5 exposure map, combining the mirror vignetting, detector efficiency, bad pixels and CCD gaps.
The PSF weighted mean of the area of the subimages (radius 60 arcseconds) in the individual-band exposure maps. real 4 s

PN_5_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 5 flux real 4 erg/cm**2/s

PN_5_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 5 flux error real 4 erg/cm**2/s

PN_5_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 5 Count rates real 4 counts/s

PN_5_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 5 Count rates error real 4 counts/s

PN_5_VIG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN band 5 vignetting value. real 4

PN_8_CTS twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Combined band source counts real 4 counts

PN_8_CTS_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Combined band source counts 1 σ error real 4 counts

PN_8_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 8 Maximum likelihood real 4

PN_8_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 8 flux real 4 erg/cm**2/s

PN_8_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 8 flux error real 4 erg/cm**2/s

PN_8_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 8 Count rates real 4 counts/s

PN_8_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 8 Count rates error real 4 counts/s

PN_9_DET_ML twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 9 Maximum likelihood real 4

PN_9_FLUX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 9 flux real 4 erg/cm**2/s

PN_9_FLUX_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 9 flux error real 4 erg/cm**2/s

PN_9_RATE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 9 Count rates real 4 counts/s

PN_9_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM PN band 9 Count rates error real 4 counts/s

PN_CHI2PROB twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM The Chi² probability (based on the null hypothesis) that the source as detected by the PN camera is constant.
The Pearson approximation to Chi² for Poissonian data was used, in which the model is used as the estimator of its own variance . If more than one exposure (that is, time series) is available for this source the smallest value of probability was used. real 4

PN_CHI2PROB xmm3dr4 XMM The Chi² probability (based on the null hypothesis) that the source as detected by the PN camera is constant.
The Pearson approximation to Chi² for Poissonian data was used, in which the model is used as the estimator of its own variance . If more than one exposure (that is, time series) is available for this source the smallest value of probability was used. float 8

PN_FILTER twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM PN filter. The options are Thick, Medium, Thin1, Thin2, and Open, depending on the efficiency of the optical blocking. varchar 6

PN_FILTER xmm3dr4 XMM PN filter. The options are Thick, Medium, Thin1, Thin2, and Open, depending on the efficiency of the optical blocking. varchar 50

PN_FLAG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM PN flag string made of the flags 1 - 12 (counted from left to right) for the PN source detection.
In case where the camera was not used in the source detection a dash is given. In case a source was not detected by the PN the flags are all set to False (default). Flag 10 is not used. varchar 12

PN_FLAG xmm3dr4 XMM PN flag string made of the flags 1 - 12 (counted from left to right) for the PN source detection.
In case where the camera was not used in the source detection a dash is given. In case a source was not detected by the PN the flags are all set to False (default). Flag 10 is not used. varchar 50

PN_FVAR xmm3dr4 XMM The fractional excess variance measured in the PN timeseries of the detection. Where multiple PN exposures exist, it is for the one giving the largest probability of variability (PN_CHI2PROB). This quantity provides a measure of the amplitude of variability in the timeseries, above purely statistical fluctuations. float 8

PN_FVARERR xmm3dr4 XMM The error on the fractional excess variance for the PN timeseries of the detection (PN_FVAR). float 8

PN_HR1 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN hardness ratio between the bands 1 & 2
In the case where the rate in one band is 0.0 (i.e., too faint to be detected in this band) the hardness ratio will be -1 or +1 which is only a lower or upper limit, respectively. real 4

PN_HR1_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The 1 σ error of the PN hardness ratio between the bands 1 & 2 real 4

PN_HR2 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN hardness ratio between the bands 2 & 3
In the case where the rate in one band is 0.0 (i.e., too faint to be detected in this band) the hardness ratio will be -1 or +1 which is only a lower or upper limit, respectively. real 4

PN_HR2_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The 1 σ error of the PN hardness ratio between the bands 2 & 3 real 4

PN_HR3 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN hardness ratio between the bands 3 & 4
In the case where the rate in one band is 0.0 (i.e., too faint to be detected in this band) the hardness ratio will be -1 or +1 which is only a lower or upper limit, respectively. real 4

PN_HR3_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The 1 σ error of the PN hardness ratio between the bands 3 & 4 real 4

PN_HR4 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN hardness ratio between the bands 4 & 5
In the case where the rate in one band is 0.0 (i.e., too faint to be detected in this band) the hardness ratio will be -1 or +1 which is only a lower or upper limit, respectively. real 4

PN_HR4_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The 1 σ error of the PN hardness ratio between the bands 4 & 5 real 4

PN_MASKFRAC twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PSF weighted mean of the detector coverage of a detection as derived from the detection mask.
Sources which have less than 0.15 of their PSF covered by the detector are considered as being not detected. real 4

PN_OFFAX twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN offaxis angle (the distance between the detection position and the onaxis position on the respective detector).
The offaxis angle for a camera can be larger than 15 arcminutes when the detection is located outside the FOV of that camera. real 4 arcmin

PN_ONTIME twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM The PN ontime value (the total good exposure time (after GTI filtering) of the CCD where the detection is positioned).
If a source position falls into CCD gaps or outside of the detector it will have a NULL given. real 4 s

PN_SUBMODE twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 XMM PN observing mode. The options are full frame mode with the full FOV exposed (in two sub-modes), and large window mode with only parts of the FOV exposed. varchar 23

PN_SUBMODE xmm3dr4 XMM PN observing mode. The options are full frame mode with the full FOV exposed (in two sub-modes), and large window mode with only parts of the FOV exposed. varchar 50

pNearH iras_psc IRAS Number of nearby hours-confirmed point sources tinyint 1 NUMBER

pNearW iras_psc IRAS Number of nearby weeks-confirmed point sources tinyint 1 NUMBER

pNoise calSource, calSynopticSource WSACalib Probability that the source is noise real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pNoise dxsJKsource, gcsPointSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, lasExtendedSource, lasPointSource, lasYJHKsource, reliableDxsSource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource, reliableUdsSource WSA Probability that the source is noise real 4 STAT_PROP

pNoise dxsSource, gcsSource, gpsSource, lasSource, udsSource WSA Probability that the source is noise real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pNoise lasYselJSourceRemeasurement WSA Probability that the source is noise real 4 stat.probability

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pNoise uhsSource, uhsSourceAll WSAUHS Probability that the source is noise real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pointingID Multiframe WSA Pointing ID within survey {image primary HDU keyword: SURVEY_I} varchar 64 NONE ??

pointingID Multiframe WSACalib Pointing ID within survey {image primary HDU keyword: SURVEY_I} varchar 64 NONE ??

pointingID Multiframe WSATransit Pointing ID within survey {image primary HDU keyword: SURVEY_I} varchar 64 NONE ??

pointingID Multiframe WSAUHS Pointing ID within survey {image primary HDU keyword: SURVEY_I} varchar 64 NONE ??

polFlux nvssSource NVSS Integrated linearly polarized flux density real 4 mJy PHOT_FLUX_LINEAR

polPA nvssSource NVSS [-90,90] The position angle of polFlux real 4 degress POS_POS-EQ

pos iras_asc IRAS Position Angle from IRAS Source to Association (E of N) smallint 2 degrees POS_POS-ANG

posAng iras_psc IRAS Uncertainty ellipse position angle (East of North) smallint 2 degrees POS_POS-ANG

posAngle CurrentAstrometry WSACalib orientation of image x-axis to N-S float 8 Degrees -0.9999995e9 pos.posAng

posAngle CurrentAstrometry WSATransit orientation of image x-axis to N-S float 8 Degrees -0.9999995e9 pos.posAng

posAngle CurrentAstrometry WSAUHS orientation of image x-axis to N-S float 8 Degrees -0.9999995e9 pos.posAng

posAngle CurrentAstrometry, PreviousAstrometry WSA orientation of image x-axis to N-S float 8 Degrees -0.9999995e9 pos.posAng

posAngle Detection PS1DR2 Position angle (sky-to-chip) at this location. real 4 degrees -999

posAngle RequiredMosaic WSACalib Orientation of image x-axis to N-S real 4 deg -0.9999995e9

posAngle RequiredMosaic WSATransit Orientation of image x-axis to N-S real 4 deg -0.9999995e9

posAngle RequiredMosaic WSAUHS Orientation of image x-axis to N-S real 4 deg -0.9999995e9

posAngle RequiredMosaic, RequiredRegion WSA Orientation of image x-axis to N-S real 4 deg -0.9999995e9

POSCOROK xmm3dr4 XMM Signifies whether catcorr obtained a statistically reliable solution or not (0 = False, 1 = True). This parameter is redundant in the sense that if REFCAT is positive, then a reliable solution was considered to have been found. bit 1

POSERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0, xmm3dr4 XMM Total position uncertainty in arcseconds calculated by combining the statistical error RADEC_ERR and the systematic error SYSERR as follows: POSERR = SQRT ( RADEC_ERR² + SYSERR² ). real 4 arcsec

posflg tycho2 GAIADR1 Type of Tycho2 solution varchar 1 meta.id;stat.fit

posMeanChisq ObjectThin PS1DR2 Reduced chi squared value of mean position. real 4 -999 stat.stdev

ppErrBits dxsOrphan, gcsOrphan, gpsOrphan, lasOrphan, UKIDSSDetection, udsOrphan WSA additional WFAU post-processing error bits int 4 0 CODE_MISC

ppErrBits calDetection WSACalib additional WFAU post-processing error bits 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.

ppErrBits dxsDetection, gcsDetection, gpsDetection, lasDetection, udsDetection WSA additional WFAU post-processing error bits 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.

ppErrBits lasMapRemeasAver WSA additional WFAU post-processing error bits based on combining average pawprint and tile flagging int 4 0 meta.code

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.

ppErrBits lasMapRemeasurement WSA additional WFAU post-processing error bits int 4 0 meta.code

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.

ppErrBits ptsDetection WSATransit additional WFAU post-processing error bits 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.

ppErrBits uhsDetection, uhsDetectionAll WSAUHS additional WFAU post-processing error bits 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.

ppErrBits uhsOrphan WSAUHS additional WFAU post-processing error bits int 4 0 CODE_MISC

ppErrBitsStatus MapFrameStatus WSA Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme and this map product. int 4 0

ppErrBitsStatus MapFrameStatus WSAUHS Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme and this map product. int 4 0

ppErrBitsStatus ProgrammeFrame WSA Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme. int 4 0

ppErrBitsStatus ProgrammeFrame WSACalib Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme. int 4 0

ppErrBitsStatus ProgrammeFrame WSATransit Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme. int 4 0

ppErrBitsStatus ProgrammeFrame WSAUHS Bit flag to denote whether detection quality flagging has been done on this multiframe for this programme. int 4 0

priam_flags gaia_source GAIADR2 Flags from Apsis-Priam analysis bigint 8 meta.code

priFlgLb rosat_bsc, rosat_fsc ROSAT priority flag L-broad tinyint 1 CODE_MISC

priFlgLh rosat_bsc, rosat_fsc ROSAT priority flag L-hard tinyint 1 CODE_MISC

priFlgLs rosat_bsc, rosat_fsc ROSAT priority flag L-soft tinyint 1 CODE_MISC

priFlgMb rosat_bsc, rosat_fsc ROSAT priority flag M-broad tinyint 1 CODE_MISC

priFlgMh rosat_bsc, rosat_fsc ROSAT priority flag M-hard tinyint 1 CODE_MISC

priFlgMs rosat_bsc, rosat_fsc ROSAT priority flag M-soft tinyint 1 CODE_MISC

primaryDetection StackObjectAttributes, StackObjectThin PS1DR2 Identifies if this row is the primary stack detection. tinyint 1 255

priOrSec calSource WSACalib Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates). bigint 8 -99999999 CODE_MISC

Because of the spacing of the detectors in WFCAM, and the restrictions on guide star brightness, there will always be overlap regions between adjacent frame sets. Source merging is done on a set-by-set basis; hence after source merging there are usually a small number of duplicate sources in the table. A process known as seaming takes place after source merging is complete, whereby duplicates are identified and flagged. The flagging attribute is priOrSec, and the meaning of the flag is quite simple: if a source is not found to be duplicated in overlap regions, then priOrSec=0; if a source is duplicated, then priOrSec will be set to the frameSetID of the source that should be considered the best one to use out of the set of duplicates. Presently, the choice of which is best is made on the basis of proximity to the optical axis of the camera, the assumption being that this will give the best quality image in general. So, if a particular source has a non-zero priOrSec that is set to it's own value of frameSetID, then this indicates that there is a duplicate elsewhere in the table, but this is the one that should be selected as the best (i.e. this is the primary source). On the other hand, if a source has a non-zero value of priOrSec that is set a different frameSetID than that of the source in question, then this indicates that this source should be considered as a secondary duplicate of a source who's primary is actually to be found in the frame set pointed to by that value of frameSetID. Hence, the WHERE clause for selecting out a seamless, best catalogue is of the form WHERE ... AND (priOrSec=0 OR priOrSec=frameSetID).

priOrSec dxsJKsource, gcsPointSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, lasExtendedSource, lasPointSource, lasYJHKsource, reliableDxsSource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource, reliableUdsSource WSA Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates). bigint 8 -99999999 CODE_MISC

priOrSec dxsSource, gcsSource, gpsSource, lasSource, udsSource WSA Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates). bigint 8 -99999999 CODE_MISC

Because of the spacing of the detectors in WFCAM, and the restrictions on guide star brightness, there will always be overlap regions between adjacent frame sets. Source merging is done on a set-by-set basis; hence after source merging there are usually a small number of duplicate sources in the table. A process known as seaming takes place after source merging is complete, whereby duplicates are identified and flagged. The flagging attribute is priOrSec, and the meaning of the flag is quite simple: if a source is not found to be duplicated in overlap regions, then priOrSec=0; if a source is duplicated, then priOrSec will be set to the frameSetID of the source that should be considered the best one to use out of the set of duplicates. Presently, the choice of which is best is made on the basis of proximity to the optical axis of the camera, the assumption being that this will give the best quality image in general. So, if a particular source has a non-zero priOrSec that is set to it's own value of frameSetID, then this indicates that there is a duplicate elsewhere in the table, but this is the one that should be selected as the best (i.e. this is the primary source). On the other hand, if a source has a non-zero value of priOrSec that is set a different frameSetID than that of the source in question, then this indicates that this source should be considered as a secondary duplicate of a source who's primary is actually to be found in the frame set pointed to by that value of frameSetID. Hence, the WHERE clause for selecting out a seamless, best catalogue is of the form WHERE ... AND (priOrSec=0 OR priOrSec=frameSetID).

priOrSec lasYselJSourceRemeasurement WSA Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates). bigint 8 -99999999 meta.code

Because of the spacing of the detectors in WFCAM, and the restrictions on guide star brightness, there will always be overlap regions between adjacent frame sets. Source merging is done on a set-by-set basis; hence after source merging there are usually a small number of duplicate sources in the table. A process known as seaming takes place after source merging is complete, whereby duplicates are identified and flagged. The flagging attribute is priOrSec, and the meaning of the flag is quite simple: if a source is not found to be duplicated in overlap regions, then priOrSec=0; if a source is duplicated, then priOrSec will be set to the frameSetID of the source that should be considered the best one to use out of the set of duplicates. Presently, the choice of which is best is made on the basis of proximity to the optical axis of the camera, the assumption being that this will give the best quality image in general. So, if a particular source has a non-zero priOrSec that is set to it's own value of frameSetID, then this indicates that there is a duplicate elsewhere in the table, but this is the one that should be selected as the best (i.e. this is the primary source). On the other hand, if a source has a non-zero value of priOrSec that is set a different frameSetID than that of the source in question, then this indicates that this source should be considered as a secondary duplicate of a source who's primary is actually to be found in the frame set pointed to by that value of frameSetID. Hence, the WHERE clause for selecting out a seamless, best catalogue is of the form WHERE ... AND (priOrSec=0 OR priOrSec=frameSetID).

priOrSec uhsSource, uhsSourceAll WSAUHS Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates). bigint 8 -99999999 CODE_MISC

Because of the spacing of the detectors in WFCAM, and the restrictions on guide star brightness, there will always be overlap regions between adjacent frame sets. Source merging is done on a set-by-set basis; hence after source merging there are usually a small number of duplicate sources in the table. A process known as seaming takes place after source merging is complete, whereby duplicates are identified and flagged. The flagging attribute is priOrSec, and the meaning of the flag is quite simple: if a source is not found to be duplicated in overlap regions, then priOrSec=0; if a source is duplicated, then priOrSec will be set to the frameSetID of the source that should be considered the best one to use out of the set of duplicates. Presently, the choice of which is best is made on the basis of proximity to the optical axis of the camera, the assumption being that this will give the best quality image in general. So, if a particular source has a non-zero priOrSec that is set to it's own value of frameSetID, then this indicates that there is a duplicate elsewhere in the table, but this is the one that should be selected as the best (i.e. this is the primary source). On the other hand, if a source has a non-zero value of priOrSec that is set a different frameSetID than that of the source in question, then this indicates that this source should be considered as a secondary duplicate of a source who's primary is actually to be found in the frame set pointed to by that value of frameSetID. Hence, the WHERE clause for selecting out a seamless, best catalogue is of the form WHERE ... AND (priOrSec=0 OR priOrSec=frameSetID).

probGal wiseScosSvm WISExSCOSPZ Probability of being a galaxy {image primary HDU keyword: pgal} real 4 -0.9999995e9

probQso wiseScosSvm WISExSCOSPZ Probability of being a QSO {image primary HDU keyword: pqso} real 4 -0.9999995e9

probStar wiseScosSvm WISExSCOSPZ Probability of being a star {image primary HDU keyword: pstar} real 4 -0.9999995e9

processingVersion Detection, StackObjectThin PS1DR2 Data release version. tinyint 1

processingVersion ObjectThin PS1DR2 Data release version. tinyint 1 meta.id;meta.software

productID EpochFrameStatus WSAUHS Product ID of deep stack frame (or intermediate stack if used as a deep stack). {image primary HDU keyword: PRODID} bigint 8 -99999999

productID EpochFrameStatus, ProgrammeFrame WSA Product ID of deep stack frame (or intermediate stack if used as a deep stack). {image primary HDU keyword: PRODID} bigint 8 -99999999

productID RequiredDiffImage WSA A unique identifier assigned to each required difference image product entry int 4 ??

productID RequiredDiffImage WSACalib A unique identifier assigned to each required difference image product entry int 4 ??

productID RequiredDiffImage WSATransit A unique identifier assigned to each required difference image product entry int 4 ??

productID RequiredDiffImage WSAUHS A unique identifier assigned to each required difference image product entry int 4 ??

productID RequiredMergeLogMultiEpoch WSAUHS A unique identifier assigned to each required stack product entry int 4 ??

productID RequiredMergeLogMultiEpoch, RequiredStack WSA A unique identifier assigned to each required stack product entry int 4 ??

productID RequiredMosaic WSA A unique identifier assigned to each required mosaic product entry int 4 ??

productID RequiredMosaic WSACalib A unique identifier assigned to each required mosaic product entry int 4 ??

productID RequiredMosaic WSATransit A unique identifier assigned to each required mosaic product entry int 4 ??

productID RequiredMosaic WSAUHS A unique identifier assigned to each required mosaic product entry int 4 ??

productType EpochFrameStatus WSA Product type (stack,tile,mosaic) varchar 16 NONE

productType EpochFrameStatus WSAUHS Product type (stack,tile,mosaic) varchar 16 NONE

productType ExternalProduct WSA The product type within the imported directory varchar 16 ??

productType ExternalProduct WSAUHS The product type within the imported directory varchar 16 ??

productType RequiredMergeLogMultiEpoch WSA Product type (stack,tile,mosaic) varchar 16

productType RequiredMergeLogMultiEpoch WSAUHS Product type (stack,tile,mosaic) varchar 16

programmeID EpochFrameStatus WSA WSA assigned programme UID {image primary HDU keyword: HIERARCH ESO OBS PROG ID} int 4 -99999999 meta.id

programmeID EpochFrameStatus WSAUHS WSA assigned programme UID {image primary HDU keyword: HIERARCH ESO OBS PROG ID} int 4 -99999999 meta.id

programmeID ExternalProduct, ProductLinks, ProgrammeCurationHistory, ProgrammeTable, RequiredDiffImage, RequiredFilters, RequiredMapAverages, RequiredMergeLogMultiEpoch, RequiredMosaic, RequiredNeighbours, RequiredRegion, RequiredStack WSA the unique programme ID int 4 meta.id

programmeID ExternalProduct, RequiredMosaic, RequiredMosaicTopLevel WSAUHS the unique programme ID int 4 meta.id

programmeID MapFrameStatus WSA WSA assigned programme UID int 4 -99999999 ID_SURVEY

programmeID MapFrameStatus WSAUHS WSA assigned programme UID int 4 -99999999 ID_SURVEY

programmeID ProblemFrames WSA VSA assigned programme UID int 4 -99999999 meta.id

programmeID ProblemFrames WSAUHS VSA assigned programme UID int 4 -99999999 meta.id

programmeID Programme WSA UID of the archived programme coded as above int 4 meta.id

programmeID Programme WSACalib UID of the archived programme coded as above int 4 meta.id

programmeID Programme WSATransit UID of the archived programme coded as above int 4 meta.id

programmeID Programme WSAUHS UID of the archived programme coded as above int 4 meta.id

programmeID ProgrammeFrame WSACalib WSA assigned programme UID {image primary HDU keyword: PROJECT} int 4 -99999999 meta.id

programmeID ProgrammeFrame WSATransit WSA assigned programme UID {image primary HDU keyword: PROJECT} int 4 -99999999 meta.id

programmeID ProgrammeFrame WSAUHS WSA assigned programme UID {image primary HDU keyword: PROJECT} int 4 -99999999 meta.id

programmeID ProgrammeFrame, SurveyProgrammes WSA WSA assigned programme UID {image primary HDU keyword: PROJECT} int 4 -99999999 meta.id

programmeID RequiredMatchedApertureProduct WSA the unique programme ID int 4 ID_SURVEY

programmeID RequiredMatchedApertureProduct WSAUHS the unique programme ID int 4 ID_SURVEY

project Multiframe WSA Time-allocation code {image primary HDU keyword: PROJECT} varchar 64 NONE meta.bib

project Multiframe WSACalib Time-allocation code {image primary HDU keyword: PROJECT} varchar 64 NONE meta.bib

project Multiframe WSATransit Time-allocation code {image primary HDU keyword: PROJECT} varchar 64 NONE meta.bib

project Multiframe WSAUHS Time-allocation code {image primary HDU keyword: PROJECT} varchar 64 NONE meta.bib

projectionID ObjectThin PS1DR2 Projection cell identifier. smallint 2 -1 meta.id

projectionID StackObjectThin PS1DR2 Projection cell identifier. smallint 2 -1

propPeriod Programme WSA the proprietory period for any data taken for this programme in months, e.g. 12 for open time. int 4 months time.period

propPeriod Programme WSACalib the proprietory period for any data taken for this programme in months, e.g. 12 for open time. int 4 months time.period

propPeriod Programme WSATransit the proprietory period for any data taken for this programme in months, e.g. 12 for open time. int 4 months time.period

propPeriod Programme WSAUHS the proprietory period for any data taken for this programme in months, e.g. 12 for open time. int 4 months time.period

proprietary Survey WSA Logical flag indicating whether a survey is proprietary or not (1=yes; 0=no) tinyint 1 ??

proprietary Survey WSACalib Logical flag indicating whether a survey is proprietary or not (1=yes; 0=no) tinyint 1 ??

proprietary Survey WSATransit Logical flag indicating whether a survey is proprietary or not (1=yes; 0=no) tinyint 1 ??

proprietary Survey WSAUHS Logical flag indicating whether a survey is proprietary or not (1=yes; 0=no) tinyint 1 ??

prox twomass_psc, twomass_xsc 2MASS Proximity. real 4 arcsec POS_ANG_DIST_GENERAL

prox tycho2 GAIADR1 Proximity indicator smallint 2 0.1 arcsec pos.angDistance

pSaturated calSource, calSynopticSource WSACalib Probability that the source is saturated real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pSaturated dxsJKsource, gcsPointSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, lasExtendedSource, lasPointSource, lasYJHKsource, reliableDxsSource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource, reliableUdsSource WSA Probability that the source is saturated real 4 STAT_PROP

pSaturated dxsSource, gcsSource, gpsSource, lasSource, udsSource WSA Probability that the source is saturated real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pSaturated lasYselJSourceRemeasurement WSA Probability that the source is saturated real 4 stat.probability

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pSaturated uhsSource, uhsSourceAll WSAUHS Probability that the source is saturated real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pseudocolour gaia_source GAIAEDR3 Astrometrically determined pseudocolour of the source real 4 micron^-1 em.wavenumber

pseudocolour_error gaia_source GAIAEDR3 STandard error of the pseudocolour of the source real 4 micron^-1 em.wavenumber

psfChiSq Detection PS1DR2 Reduced chi squared value of the PSF model fit. real 4 -999

psfCore Detection PS1DR2 PSF core parameter k, where F = F0 / (1 + k r^2 + r^3.33). real 4 -999

psfFitChi2 UKIDSSDetection WSA standard normalised variance of PSF fit real 4 -0.9999995e9 FIT_STDEV

psfFitChi2 calDetection WSACalib standard normalised variance of PSF fit {catalogue TType keyword: PSF_fit_chi2} real 4 -0.9999995e9 FIT_STDEV

psfFitChi2 dxsDetection, gcsDetection, gpsDetection, lasDetection WSA standard normalised variance of PSF fit {catalogue TType keyword: PSF_fit_chi2} real 4 -0.9999995e9 FIT_STDEV

psfFitChi2 ptsDetection WSATransit standard normalised variance of PSF fit {catalogue TType keyword: PSF_fit_chi2} real 4 -0.9999995e9 FIT_STDEV

psfFitChi2 udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_fit_chi2} real 4 -0.9999995e9

psfFitChi2 uhsDetection, uhsDetectionAll WSAUHS standard normalised variance of PSF fit {catalogue TType keyword: PSF_fit_chi2} real 4 -0.9999995e9 FIT_STDEV

psfFitDof UKIDSSDetection WSA no. of degrees of freedom of PSF fit smallint 2 -9999 STAT_N-DOF

psfFitDof calDetection WSACalib no. of degrees of freedom of PSF fit {catalogue TType keyword: PSF_fit_dof} smallint 2 -9999 STAT_N-DOF

psfFitDof dxsDetection, gcsDetection, gpsDetection, lasDetection WSA no. of degrees of freedom of PSF fit {catalogue TType keyword: PSF_fit_dof} smallint 2 -9999 STAT_N-DOF

psfFitDof ptsDetection WSATransit no. of degrees of freedom of PSF fit {catalogue TType keyword: PSF_fit_dof} smallint 2 -9999 STAT_N-DOF

psfFitDof udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_fit_dof} smallint 2 -9999

psfFitDof uhsDetection, uhsDetectionAll WSAUHS no. of degrees of freedom of PSF fit {catalogue TType keyword: PSF_fit_dof} smallint 2 -9999 STAT_N-DOF

psfFitX UKIDSSDetection WSA PSF-fitted X coordinate real 4 pixels -0.9999995e9 POS_PLATE_X

psfFitX calDetection WSACalib PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X} real 4 pixels -0.9999995e9 POS_PLATE_X

psfFitX dxsDetection, gcsDetection, gpsDetection, lasDetection WSA PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X} real 4 pixels -0.9999995e9 POS_PLATE_X

psfFitX ptsDetection WSATransit PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X} real 4 pixels -0.9999995e9 POS_PLATE_X

psfFitX udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_fit_X} real 4 -0.9999995e9

psfFitX uhsDetection, uhsDetectionAll WSAUHS PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X} real 4 pixels -0.9999995e9 POS_PLATE_X

psfFitXerr UKIDSSDetection WSA Error on PSF-fitted X coordinate real 4 pixels -0.9999995e9 ERROR

psfFitXerr calDetection WSACalib Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_err} real 4 pixels -0.9999995e9 ERROR

psfFitXerr dxsDetection, gcsDetection, gpsDetection, lasDetection WSA Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_err} real 4 pixels -0.9999995e9 ERROR

psfFitXerr ptsDetection WSATransit Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_err} real 4 pixels -0.9999995e9 ERROR

psfFitXerr udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_fit_X_err} real 4 -0.9999995e9

psfFitXerr uhsDetection, uhsDetectionAll WSAUHS Error on PSF-fitted X coordinate {catalogue TType keyword: PSF_fit_X_err} real 4 pixels -0.9999995e9 ERROR

psfFitY UKIDSSDetection WSA PSF-fitted Y coordinate real 4 pixels -0.9999995e9 POS_PLATE_Y

psfFitY calDetection WSACalib PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_Y} real 4 pixels -0.9999995e9 POS_PLATE_Y

psfFitY dxsDetection, gcsDetection, gpsDetection, lasDetection WSA PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_Y} real 4 pixels -0.9999995e9 POS_PLATE_Y

psfFitY ptsDetection WSATransit PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_Y} real 4 pixels -0.9999995e9 POS_PLATE_Y

psfFitY udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_fit_Y} real 4 -0.9999995e9

psfFitY uhsDetection, uhsDetectionAll WSAUHS PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_Y} real 4 pixels -0.9999995e9 POS_PLATE_Y

psfFitYerr UKIDSSDetection WSA Error on PSF-fitted Y coordinate real 4 pixels -0.9999995e9 ERROR

psfFitYerr calDetection WSACalib Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_err} real 4 pixels -0.9999995e9 ERROR

psfFitYerr dxsDetection, gcsDetection, gpsDetection, lasDetection WSA Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_err} real 4 pixels -0.9999995e9 ERROR

psfFitYerr ptsDetection WSATransit Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_err} real 4 pixels -0.9999995e9 ERROR

psfFitYerr udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_fit_y_err} real 4 -0.9999995e9

psfFitYerr uhsDetection, uhsDetectionAll WSAUHS Error on PSF-fitted Y coordinate {catalogue TType keyword: PSF_fit_y_err} real 4 pixels -0.9999995e9 ERROR

psfFlux Detection PS1DR2 Flux from PSF fit. real 4 Janskys -999

psfFlux UKIDSSDetection WSA PSF-fitted flux real 4 ADU -0.9999995e9 PHOT_INTENSITY_ADU

psfFlux calDetection WSACalib PSF-fitted flux {catalogue TType keyword: PSF_flux} real 4 ADU -0.9999995e9 PHOT_INTENSITY_ADU

psfFlux dxsDetection, gcsDetection, gpsDetection, lasDetection WSA PSF-fitted flux {catalogue TType keyword: PSF_flux} real 4 ADU -0.9999995e9 PHOT_INTENSITY_ADU

psfFlux ptsDetection WSATransit PSF-fitted flux {catalogue TType keyword: PSF_flux} real 4 ADU -0.9999995e9 PHOT_INTENSITY_ADU

psfFlux udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_flux} real 4 -0.9999995e9

psfFlux uhsDetection, uhsDetectionAll WSAUHS PSF-fitted flux {catalogue TType keyword: PSF_flux} real 4 ADU -0.9999995e9 PHOT_INTENSITY_ADU

psfFluxErr Detection PS1DR2 Error on flux from PSF fit. real 4 Janskys -999

psfFluxErr UKIDSSDetection WSA Error on PSF-fitted flux real 4 ADU -0.9999995e9 ERROR

psfFluxErr calDetection WSACalib Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_err} real 4 ADU -0.9999995e9 ERROR

psfFluxErr dxsDetection, gcsDetection, gpsDetection, lasDetection WSA Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_err} real 4 ADU -0.9999995e9 ERROR

psfFluxErr ptsDetection WSATransit Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_err} real 4 ADU -0.9999995e9 ERROR

psfFluxErr udsDetection WSA Not available in SE output {catalogue TType keyword: PSF_flux_err} real 4 -0.9999995e9

psfFluxErr uhsDetection, uhsDetectionAll WSAUHS Error on PSF-fitted flux {catalogue TType keyword: PSF_flux_err} real 4 ADU -0.9999995e9 ERROR

psfLikelihood Detection PS1DR2 Likelihood that this detection is best fit by a PSF. real 4 -999

psfMag dxsDetection, gcsDetection, gpsDetection, lasDetection, UKIDSSDetection WSA PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 PHOT_PROFILE

psfMag calDetection WSACalib PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 PHOT_PROFILE

psfMag ptsDetection WSATransit PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 PHOT_PROFILE

psfMag udsDetection WSA Not available in SE output real 4 -0.9999995e9

psfMag uhsDetection, uhsDetectionAll WSAUHS PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 PHOT_PROFILE

psfMagErr dxsDetection, gcsDetection, gpsDetection, lasDetection, UKIDSSDetection WSA Error on PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 ERROR

psfMagErr calDetection WSACalib Error on PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 ERROR

psfMagErr ptsDetection WSATransit Error on PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 ERROR

psfMagErr udsDetection WSA Not available in SE output real 4 -0.9999995e9

psfMagErr uhsDetection, uhsDetectionAll WSAUHS Error on PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 ERROR

psfMajorFWHM Detection PS1DR2 PSF major axis FWHM. real 4 arcsec -999

psfMinorFWHM Detection PS1DR2 PSF minor axis FWHM. real 4 arcsec -999

psfQf Detection PS1DR2 PSF coverage factor. real 4 -999

psfQfPerfect Detection PS1DR2 PSF weighted fraction of pixels totally unmasked. real 4 -999

psfTheta Detection PS1DR2 PSF major axis orientation. real 4 degrees -999

pStar calSource, calSynopticSource WSACalib Probability that the source is a star real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pStar dxsJKsource, gcsPointSource, gcsZYJHKsource, gpsJHKsource, gpsPointSource, lasExtendedSource, lasPointSource, lasYJHKsource, reliableDxsSource, reliableGcsPointSource, reliableGpsPointSource, reliableLasPointSource, reliableUdsSource WSA Probability that the source is a star real 4 STAT_PROP

pStar dxsSource, gcsSource, gpsSource, lasSource, udsSource WSA Probability that the source is a star real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pStar lasYselJSourceRemeasurement WSA Probability that the source is a star real 4 stat.probability

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pStar uhsSource, uhsSourceAll WSAUHS Probability that the source is a star real 4 STAT_PROP

Individual detection classifications are combined in the source merging process to produce a set of attributes for each merged source as follows. Presently, a basic classification table is defined that assigns reasonably accurate, self-consistent probability values for a given classification code:

Flag Meaning Probability (%)

Star Galaxy Noise Saturated

-9 Saturated 0.0 0.0 5.0 95.0

-3 Probable galaxy 25.0 70.0 5.0 0.0

-2 Probable star 70.0 25.0 5.0 0.0

-1 Star 90.0 5.0 5.0 0.0

0 Noise 5.0 5.0 90.0 0.0

+1 Galaxy 5.0 90.0 5.0 0.0

Then, each separately available classification is combined for a merged source using Bayesian classification rules, assuming each datum is independent:

P(class_k)=Π_iP(class_k)_i / Σ_kΠ_iP(class_k)_i
where class_k is one of star|galaxy|noise|saturated, and i denotes the i^th single detection passband measurement available (the non-zero entries are necessary for the independent measures method to work, since some cases might otherwise be mutually exclusive). For example, if an object is classed in J|H|K as -1|-2|+1 it would have merged classification probabilities of pStar=73.5%, pGalaxy=26.2%, pNoise=0.3% and pSaturated=0.0%. Decision thresholds for the resulting discrete classification flag mergedClass are 90% for definitive and 70% for probable; hence the above example would be classified (not unreasonably) as probably a star (mergedClass=-2). An additional decision rule enforces mergedClass=-9 (saturated) when any individual classification flag indicates saturation.

pts_key twomass_psc 2MASS A unique identification number for the PSC source. int 4 ID_NUMBER

pts_key twomass_xsc 2MASS key to point source data DB record. int 4 ID_NUMBER

publicDb Release WSA the name of the SQL Server database containing the public release varchar 128 NONE ??

publicDb Release WSACalib the name of the SQL Server database containing the public release varchar 128 NONE ??

publicDb Release WSATransit the name of the SQL Server database containing the public release varchar 128 NONE ??

publicDb Release WSAUHS the name of the SQL Server database containing the public release varchar 128 NONE ??

pv21 CurrentAstrometry WSACalib Coefficient for r term (use only with ZPN projection) {image extension keyword: PV2_1}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv21 CurrentAstrometry WSATransit Coefficient for r term (use only with ZPN projection) {image extension keyword: PV2_1}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv21 CurrentAstrometry WSAUHS Coefficient for r term (use only with ZPN projection) {image extension keyword: PV2_1}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv21 CurrentAstrometry, PreviousAstrometry WSA Coefficient for r term (use only with ZPN projection) {image extension keyword: PV2_1}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv22 CurrentAstrometry WSACalib Coefficient for r**2 term (use only with ZPN projection) {image extension keyword: PV2_2}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv22 CurrentAstrometry WSATransit Coefficient for r**2 term (use only with ZPN projection) {image extension keyword: PV2_2}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv22 CurrentAstrometry WSAUHS Coefficient for r**2 term (use only with ZPN projection) {image extension keyword: PV2_2}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv22 CurrentAstrometry, PreviousAstrometry WSA Coefficient for r**2 term (use only with ZPN projection) {image extension keyword: PV2_2}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv23 CurrentAstrometry WSACalib Coefficient for r**3 term (use only with ZPN projection) {image extension keyword: PV2_3}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv23 CurrentAstrometry WSATransit Coefficient for r**3 term (use only with ZPN projection) {image extension keyword: PV2_3}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv23 CurrentAstrometry WSAUHS Coefficient for r**3 term (use only with ZPN projection) {image extension keyword: PV2_3}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pv23 CurrentAstrometry, PreviousAstrometry WSA Coefficient for r**3 term (use only with ZPN projection) {image extension keyword: PV2_3}
transformation from pixel to celestial co-ordinates float 8 -0.9999995e9 stat.fit.param

pxcntr twomass_psc 2MASS The pts_key value of the nearest source in the PSC. int 4 NUMBER

pxcntr twomass_xsc 2MASS ext_key value of nearest XSC source. int 4 NUMBER

pxpa twomass_psc, twomass_xsc 2MASS The position angle on the sky of the vector from the source to the nearest neighbor in the PSC, in degrees East of North. smallint 2 degrees POS_POS-ANG

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

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