WSA Browser

Glossary of WSA attributes

This Glossary alphabetically lists all attributes used in the UKIDSSDR8 database(s) held in the WSA. If you would like to have more information about the schema tables please use the UKIDSSDR8 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

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, calListRemeasurement 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, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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 FIRST position angle (east of north) derived from the elliptical Gaussian model for the source real 4 degrees POS_POS-ANG

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

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 ??

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, 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.

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 ??

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

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

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

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

petroFluxErr UKIDSSDetection WSA error on Petrosian flux real 4 ADU ERROR

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

petroFluxErr dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement WSA error on Petrosian flux {catalogue TType keyword: Petr_flux_err} real 4 ADU 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

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

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

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

petroMagErr dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, UKIDSSDetection, udsDetection, udsListRemeasurement WSA error on calibrated Petrosian magnitude real 4 mag ERROR

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

petroMagErr ptsDetection WSATransit 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, calListRemeasurement 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, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement WSA r_p as defined in Yasuda et al. 2001 AJ 112 1104 {catalogue TType keyword: Petr_radius} real 4 pixels EXTENSION_RAD

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.

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

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.

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

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, calListRemeasurement 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, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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 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

pHeightErr UKIDSSDetection WSA Error in peak height real 4 ADU ERROR

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

pHeightErr dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement WSA Error in peak height {catalogue TType keyword: Peak_height_err} real 4 ADU 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

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

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 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

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 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

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 INST_PIXSIZE

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 INST_PIXSIZE

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 INST_PIXSIZE

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 ??

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

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

PN_1_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 1 Maximum likelihood real 4

PN_1_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 1 flux real 4 erg/cm**2/s

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

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

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

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

PN_2_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 2 Maximum likelihood real 4

PN_2_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 2 flux real 4 erg/cm**2/s

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

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

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

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

PN_3_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 3 Maximum likelihood real 4

PN_3_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 3 flux real 4 erg/cm**2/s

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

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

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

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

PN_4_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 4 Maximum likelihood real 4

PN_4_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 4 flux real 4 erg/cm**2/s

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

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

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

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

PN_5_BG twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 5 Maximum likelihood real 4

PN_5_EXP twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 XMM PN band 5 flux real 4 erg/cm**2/s

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

PN_9_RATE_ERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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_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_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_HR1 twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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 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 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 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 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 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 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 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 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 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 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

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.

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 ??

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_POS-ANG

posAngle CurrentAstrometry WSATransit orientation of image x-axis to N-S float 8 Degrees -0.9999995e9 POS_POS-ANG

posAngle CurrentAstrometry, PreviousAstrometry WSA orientation of image x-axis to N-S float 8 Degrees -0.9999995e9 POS_POS-ANG

POSERR twoxmm, twoxmm_v1_2, twoxmmi_dr3_v1_0 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

ppErrBits dxsListRemeasurement, gcsListRemeasurement, gpsListRemeasurement, lasListRemeasurement, UKIDSSDetection, udsListRemeasurement 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

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 calListRemeasurement WSACalib additional WFAU post-processing error bits int 4 0 CODE_MISC

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

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

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.

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

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

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 calSourceRemeasurement WSACalib Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates) bigint 8 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 dxsSourceRemeasurement, gcsSourceRemeasurement, gpsSourceRemeasurement, lasSourceRemeasurement, udsSourceRemeasurement WSA Seam code for a unique (=0) or duplicated (!=0) source (eg. flags overlap duplicates) bigint 8 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).

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

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

productID RequiredStack WSACalib A unique identifier assigned to each required stack product entry int 4 ??

productID RequiredStack WSATransit A unique identifier assigned to each required stack product entry int 4 ??

programmeID ProductLinks, ProgrammeCurationHistory, ProgrammeTable, RequiredDiffImage, RequiredFilters, RequiredListDrivenProduct, RequiredMosaic, RequiredNeighbours, RequiredStack WSA the unique programme ID int 4 ID_SURVEY

programmeID Programme WSA UID of the archived programme coded as above int 4 ID_SURVEY

programmeID Programme WSACalib UID of the archived programme coded as above int 4 ID_SURVEY

programmeID Programme WSATransit UID of the archived programme coded as above int 4 ID_SURVEY

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

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

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

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

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

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

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

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 ??

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

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.

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

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

psfFitChi2 dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFitDof dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFitX dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFitXerr dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFitY dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFitYerr dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFlux dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

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

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

psfFluxErr dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, udsListRemeasurement 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

psfMag dxsDetection, dxsListRemeasurement, gcsDetection, gcsListRemeasurement, gpsDetection, gpsListRemeasurement, lasDetection, lasListRemeasurement, UKIDSSDetection, udsListRemeasurement WSA PSF-fitted calibrated magnitude real 4 mag -0.9999995e9 PHOT_PROFILE

psfMag calDetection, calListRemeasurement 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

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

psfMagErr calDetection, calListRemeasurement 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

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.

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

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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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 POS_TRANSF_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
Tel +44 131 668 8356 (office)
or +44 131 668 8100 (switchboard)

wsa-support@roe.ac.uk
12/05/2011