tractor/<AAA>/tractor-<brick>.fits
FITS binary table containing Tractor photometry. Before using these catalogs, note that there may be known issues regarding their content and derivation. The columns pertaining to optical data also have \(u\), \(i\) and \(Y\)-band entries (e.g. flux_u, flux_i, flux_Y), but these contain only zeros.
Name | Type | Units | Description |
---|---|---|---|
release | int16 | Unique integer denoting the camera and filter set used (RELEASE is documented here) | |
brickid | int32 | Brick ID [1,662174] | |
brickname | char[8] | Name of brick, encoding the brick sky position, eg "1126p222" near RA=112.6, Dec=+22.2 | |
objid | int32 | Catalog object number within this brick; a unique identifier hash is BRICKID,OBJID; OBJID spans [0,N-1] and is contiguously enumerated within each blob | |
brick_primary | boolean | True if the object is within the brick boundary | |
brightstarinblob | boolean | True if the object shares a blob with a "bright" (Tycho-2) star | |
type | char[4] | Morphological model: "PSF"=stellar, "REX"="round exponential galaxy", "DEV"=deVauc, "EXP"=exponential, "COMP"=composite. Note that in some FITS readers, a trailing space may be appended for "PSF ", "DEV " and "EXP " since the column data type is a 4-character string | |
ra | float64 | deg | Right ascension at epoch J2000 |
dec | float64 | deg | Declination at epoch J2000 |
ra_ivar | float32 | 1/deg² | Inverse variance of RA (no cosine term!), excluding astrometric calibration errors |
dec_ivar | float32 | 1/deg² | Inverse variance of DEC, excluding astrometric calibration errors |
bx | float32 | pix | X position (0-indexed) of coordinates in brick image stack |
by | float32 | pix | Y position (0-indexed) of coordinates in brick image stack |
dchisq | float32[5] | Difference in χ² between successively more-complex model fits: PSF, REX, DEV, EXP, COMP. The difference is versus no source. | |
ebv | float32 | mag | Galactic extinction E(B-V) reddening from SFD98, used to compute DECAM_MW_TRANSMISSION and WISE_MW_TRANSMISSION |
mjd_min | float64 | days | Minimum Modified Julian Date of observations used to construct the model of this object |
mjd_max | float64 | days | Maximum Modified Julian Date of observations used to construct the model of this object |
ref_cat | char[2] | Reference catalog source for this star: "T2" for Tycho-2, "G2" for Gaia DR2, empty otherwise | |
ref_id | int64 | Reference catalog identifier for this star; Tyc1*1,000,000+Tyc2*10+Tyc3 for Tycho2; "sourceid" for Gaia-DR2 | |
pmra | float32 | mas/yr | Reference catalog proper motion in the RA direction |
pmdec | float32 | mas/yr | Reference catalog proper motion in the Dec direction |
parallax | float32 | mas | Reference catalog parallax |
pmra_ivar | float32 | 1/(mas/yr)² | Reference catalog inverse-variance on pmra |
pmdec_ivar | float32 | 1/(mas/yr)² | Reference catalog inverse-variance on pmdec |
parallax_ivar | float32 | 1/(mas)² | Reference catalog inverse-variance on parallax |
ref_epoch | float32 | yr | Reference catalog reference epoch (eg, 2015.5 for Gaia-DR2) |
gaia_pointsource | bool | This Gaia-DR2 source is believed to be a star, not a galaxy | |
gaia_phot_g_mean_mag | float32 | mag | Gaia G band mag |
gaia_phot_g_mean_flux_over_error | float32 | Gaia G band signal-to-noise | |
gaia_phot_g_n_obs | int16 | Gaia G band number of observations | |
gaia_phot_bp_mean_mag | float32 | mag | Gaia BP mag |
gaia_phot_bp_mean_flux_over_error | float32 | Gaia BP signal-to-noise | |
gaia_phot_bp_n_obs | int16 | Gaia BP number of observations | |
gaia_phot_rp_mean_mag | float32 | mag | Gaia RP mag |
gaia_phot_rp_mean_flux_over_error | float32 | Gaia RP signal-to-noise | |
gaia_phot_rp_n_obs | int16 | Gaia RP number of observations | |
gaia_phot_variable_flag | bool | Gaia photometric variable flag | |
gaia_astrometric_excess_noise | float32 | Gaia astrometric excess noise | |
gaia_astrometric_excess_noise_sig | float32 | Gaia astrometric excess noise uncertainty | |
gaia_astrometric_n_obs_al | int16 | Gaia number of astrometric observations along scan direction | |
gaia_astrometric_n_good_obs_al | int16 | Gaia number of good astrometric observations along scan direction | |
gaia_astrometric_weight_al | float32 | Gaia astrometric weight along scan direction | |
gaia_duplicated_source | bool | Gaia duplicated source flag | |
flux_g | float32 | nanomaggies | model flux in \(g\) |
flux_r | float32 | nanomaggies | model flux in \(r\) |
flux_z | float32 | nanomaggies | model flux in \(z\) |
flux_w1 | float32 | nanomaggies | WISE model flux in \(W1\) |
flux_w2 | float32 | nanomaggies | WISE model flux in \(W2\) |
flux_w3 | float32 | nanomaggies | WISE model flux in \(W3\) |
flux_w4 | float32 | nanomaggies | WISE model flux in \(W4\) |
flux_ivar_g | float32 | 1/nanomaggies² | Inverse variance of FLUX_G |
flux_ivar_r | float32 | 1/nanomaggies² | Inverse variance of FLUX_R |
flux_ivar_z | float32 | 1/nanomaggies² | Inverse variance of FLUX_Z |
flux_ivar_w1 | float32 | 1/nanomaggies² | Inverse variance of FLUX_W1 |
flux_ivar_w2 | float32 | 1/nanomaggies² | Inverse variance of FLUX_W2 |
flux_ivar_w3 | float32 | 1/nanomaggies² | Inverse variance of FLUX_W3 |
flux_ivar_w4 | float32 | 1/nanomaggies² | Inverse variance of FLUX_W4 |
fiberflux_g | float32 | nanomaggies | Predicted \(g\)-band flux within a fiber from this object in 1 arcsec Gaussian seeing |
fiberflux_r | float32 | nanomaggies | Predicted \(r\)-band flux within a fiber from this object in 1 arcsec Gaussian seeing |
fiberflux_z | float32 | nanomaggies | Predicted \(z\)-band flux within a fiber from this object in 1 arcsec Gaussian seeing |
fibertotflux_g | float32 | nanomaggies | Predicted \(g\)-band flux within a fiber from all sources at this location in 1 arcsec Gaussian seeing |
fibertotflux_r | float32 | nanomaggies | Predicted \(r\)-band flux within a fiber from all sources at this location in 1 arcsec Gaussian seeing |
fibertotflux_z | float32 | nanomaggies | Predicted \(z\)-band flux within a fiber from all sources at this location in 1 arcsec Gaussian seeing |
apflux_g | float32[8] | nanomaggies | aperture fluxes on the co-added images in apertures of radius [0.5,0.75,1.0,1.5,2.0,3.5,5.0,7.0] arcsec in \(g\) |
apflux_r | float32[8] | nanomaggies | aperture fluxes on the co-added images in apertures of radius [0.5,0.75,1.0,1.5,2.0,3.5,5.0,7.0] arcsec in \(r\) |
apflux_z | float32[8] | nanomaggies | aperture fluxes on the co-added images in apertures of radius [0.5,0.75,1.0,1.5,2.0,3.5,5.0,7.0] arcsec in \(z\) |
apflux_resid_g | float32[8] | nanomaggies | aperture fluxes on the co-added residual images in \(g\) |
apflux_resid_r | float32[8] | nanomaggies | aperture fluxes on the co-added residual images in \(r\) |
apflux_resid_z | float32[8] | nanomaggies | aperture fluxes on the co-added residual images in \(z\) |
apflux_ivar_g | float32[8] | 1/nanomaggies² | Inverse variance of APFLUX_RESID_G |
apflux_ivar_r | float32[8] | 1/nanomaggies² | Inverse variance of APFLUX_RESID_R |
apflux_ivar_z | float32[8] | 1/nanomaggies² | Inverse variance of APFLUX_RESID_Z |
mw_transmission_g | float32 | Galactic transmission in \(g\) filter in linear units [0,1] | |
mw_transmission_r | float32 | Galactic transmission in \(r\) filter in linear units [0,1] | |
mw_transmission_z | float32 | Galactic transmission in \(z\) filter in linear units [0,1] | |
mw_transmission_w1 | float32 | Galactic transmission in \(W1\) filter in linear units [0,1] | |
mw_transmission_w2 | float32 | Galactic transmission in \(W2\) filter in linear units [0,1] | |
mw_transmission_w3 | float32 | Galactic transmission in \(W3\) filter in linear units [0,1] | |
mw_transmission_w4 | float32 | Galactic transmission in \(W4\) filter in linear units [0,1] | |
nobs_g | int16 | Number of images that contribute to the central pixel in \(g\): filter for this object (not profile-weighted) | |
nobs_r | int16 | Number of images that contribute to the central pixel in \(r\): filter for this object (not profile-weighted) | |
nobs_z | int16 | Number of images that contribute to the central pixel in \(z\): filter for this object (not profile-weighted) | |
nobs_w1 | int16 | Number of images that contribute to the central pixel in \(W1\): filter for this object (not profile-weighted) | |
nobs_w2 | int16 | Number of images that contribute to the central pixel in \(W2\): filter for this object (not profile-weighted) | |
nobs_w3 | int16 | Number of images that contribute to the central pixel in \(W3\): filter for this object (not profile-weighted) | |
nobs_w4 | int16 | Number of images that contribute to the central pixel in \(W4\): filter for this object (not profile-weighted) | |
rchisq_g | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(g\) | |
rchisq_r | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(r\) | |
rchisq_z | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(z\) | |
rchisq_w1 | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(W1\) | |
rchisq_w2 | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(W2\) | |
rchisq_w3 | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(W3\) | |
rchisq_w4 | float32 | Profile-weighted χ² of model fit normalized by the number of pixels in \(W4\) | |
fracflux_g | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(g\) (typically [0,1]) | |
fracflux_r | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(r\) (typically [0,1]) | |
fracflux_z | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(z\) (typically [0,1]) | |
fracflux_w1 | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(W1\) (typically [0,1]) | |
fracflux_w2 | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(W2\) (typically [0,1]) | |
fracflux_w3 | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(W3\) (typically [0,1]) | |
fracflux_w4 | float32 | Profile-weighted fraction of the flux from other sources divided by the total flux in \(W4\) (typically [0,1]) | |
fracmasked_g | float32 | Profile-weighted fraction of pixels masked from all observations of this object in \(g\), strictly between [0,1] | |
fracmasked_r | float32 | Profile-weighted fraction of pixels masked from all observations of this object in \(r\), strictly between [0,1] | |
fracmasked_z | float32 | Profile-weighted fraction of pixels masked from all observations of this object in \(z\), strictly between [0,1] | |
fracin_g | float32 | Fraction of a source's flux within the blob in \(g\), near unity for real sources | |
fracin_r | float32 | Fraction of a source's flux within the blob in \(r\), near unity for real sources | |
fracin_z | float32 | Fraction of a source's flux within the blob in \(z\), near unity for real sources | |
anymask_g | int16 | Bitwise mask set if the central pixel from any image satisfies each condition in \(g\) | |
anymask_r | int16 | Bitwise mask set if the central pixel from any image satisfies each condition in \(r\) | |
anymask_z | int16 | Bitwise mask set if the central pixel from any image satisfies each condition in \(z\) | |
allmask_g | int16 | Bitwise mask set if the central pixel from all images satisfy each condition in \(g\) | |
allmask_r | int16 | Bitwise mask set if the central pixel from all images satisfy each condition in \(r\) | |
allmask_z | int16 | Bitwise mask set if the central pixel from all images satisfy each condition in \(z\) | |
wisemask_w1 | uint8 | W1 bright star bitmask, \(2^0\) \((2^1)\) for southward (northward) scans | |
wisemask_w2 | uint8 | W2 bright star bitmask, \(2^0\) \((2^1)\) for southward (northward) scans | |
psfsize_g | float32 | arcsec | Weighted average PSF FWHM in the \(g\) band |
psfsize_r | float32 | arcsec | Weighted average PSF FWHM in the \(r\) band |
psfsize_z | float32 | arcsec | Weighted average PSF FWHM in the \(z\) band |
psfdepth_g | float32 | 1/nanomaggies² | For a \(5\sigma\) point source detection limit in \(g\), \(5/\sqrt(\mathrm{PSFDEPTH\_G})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_G})) - 9]\) gives corresponding magnitude |
psfdepth_r | float32 | 1/nanomaggies² | For a \(5\sigma\) point source detection limit in \(g\), \(5/\sqrt(\mathrm{PSFDEPTH\_R})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_R})) - 9]\) gives corresponding magnitude |
psfdepth_z | float32 | 1/nanomaggies² | For a \(5\sigma\) point source detection limit in \(g\), \(5/\sqrt(\mathrm{PSFDEPTH\_Z})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_Z})) - 9]\) gives corresponding magnitude |
galdepth_g | float32 | 1/nanomaggies² | As for PSFDEPTH_G but for a galaxy (0.45" exp, round) detection sensitivity |
galdepth_r | float32 | 1/nanomaggies² | As for PSFDEPTH_R but for a galaxy (0.45" exp, round) detection sensitivity |
galdepth_z | float32 | 1/nanomaggies² | As for PSFDEPTH_Z but for a galaxy (0.45" exp, round) detection sensitivity |
wise_coadd_id | char[8] | unWISE coadd file name for the center of each object | |
lc_flux_w1 | float32[11] | nanomaggies | FLUX_W1 in each of up to eleven unWISE coadd epochs |
lc_flux_w2 | float32[11] | nanomaggies | FLUX_W2 in each of up to eleven unWISE coadd epochs |
lc_flux_ivar_w1 | float32[11] | 1/nanomaggies² | Inverse variance of LC_FLUX_W1 |
lc_flux_ivar_w2 | float32[11] | 1/nanomaggies² | Inverse variance of LC_FLUX_W2 |
lc_nobs_w1 | int16[11] | NOBS_W1 in each of up to eleven unWISE coadd epochs | |
lc_nobs_w2 | int16[11] | NOBS_W2 in each of up to eleven unWISE coadd epochs | |
lc_fracflux_w1 | float32[11] | FRACFLUX_W1 in each of up to eleven unWISE coadd epochs | |
lc_fracflux_w2 | float32[11] | FRACFLUX_W2 in each of up to eleven unWISE coadd epochs | |
lc_rchisq_w1 | float32[11] | RCHISQ_W1 in each of up to eleven unWISE coadd epochs | |
lc_rchisq_w2 | float32[11] | RCHISQ_W2 in each of up to eleven unWISE coadd epochs | |
lc_mjd_w1 | float64[11] | MJD_W1 in each of up to eleven unWISE coadd epochs | |
lc_mjd_w2 | float64[11] | MJD_W2 in each of up to eleven unWISE coadd epochs | |
fracdev | float32 | Fraction of model in deVauc [0,1] | |
fracdev_ivar | float32 | Inverse variance of FRACDEV | |
shapeexp_r | float32 | arcsec | Half-light radius of exponential model (>0) |
shapeexp_r_ivar | float32 | 1/arcsec² | Inverse variance of R_EXP |
shapeexp_e1 | float32 | Ellipticity component 1 | |
shapeexp_e1_ivar | float32 | Inverse variance of SHAPEEXP_E1 | |
shapeexp_e2 | float32 | Ellipticity component 2 | |
shapeexp_e2_ivar | float32 | Inverse variance of SHAPEEXP_E2 | |
shapedev_r | float32 | arcsec | Half-light radius of deVaucouleurs model (>0) |
shapedev_r_ivar | float32 | 1/arcsec² | Inverse variance of R_DEV |
shapedev_e1 | float32 | Ellipticity component 1 | |
shapedev_e1_ivar | float32 | Inverse variance of SHAPEDEV_E1 | |
shapedev_e2 | float32 | Ellipticity component 2 | |
shapedev_e2_ivar | float32 | Inverse variance of SHAPEDEV_E2 |
Mask Values
The ANYMASK and ALLMASK bit masks are defined as follows from the CP (NOAO Community Pipeline) Data Quality bits.
Bit | Value | Name | Description |
---|---|---|---|
0 | 1 | detector bad pixel/no data | See the CP Data Quality bit description. |
1 | 2 | saturated | See the CP Data Quality bit description. |
2 | 4 | interpolated | See the CP Data Quality bit description. |
4 | 16 | single exposure cosmic ray | See the CP Data Quality bit description. |
6 | 64 | bleed trail | See the CP Data Quality bit description. |
7 | 128 | multi-exposure transient | See the CP Data Quality bit description. |
8 | 256 | edge | See the CP Data Quality bit description. |
9 | 512 | edge2 | See the CP Data Quality bit description. |
10 | 1024 | longthin | \(\gt 5\sigma\) connected components with major axis \(\gt 200\) pixels and major/minor axis \(\gt 0.1\). To mask, e.g., satellite trails. |
Goodness-of-Fits
The dchisq values represent the χ² sum of all pixels in the source's blob for various models. This 5-element vector contains the χ² difference between the best-fit point source (type="PSF"), round exponential galaxy model ("REX"), de Vaucouleurs model ("DEV"), exponential model ("EXP"), and a composite model ("COMP"), in that order. The "REX" model is a round exponential galaxy profile with a variable radius and is meant to capture slightly-extended but low signal-to-noise objects. The dchisq values are the χ² difference versus no source in this location---that is, it is the improvement from adding the given source to our model of the sky. The first element (for PSF) corresponds to a tradition notion of detection significance. Note that the dchisq values are negated so that positive values indicate better fits. We penalize models with negative flux in a band by subtracting rather than adding its χ² improvement in that band.
The rchisq values are interpreted as the reduced χ² pixel-weighted by the model fit, computed as the following sum over pixels in the blob for each object:
The above sum is over all images contributing to a particular filter, and can be negative-valued for sources that have a flux measured as negative in some bands where they are not detected.
Galactic Extinction Coefficients
The Galactic extinction values are derived from the SFD98 maps, but with updated coefficients to convert E(B-V) to the extinction in each filter. These are reported in linear units of transmission, with 1 representing a fully transparent region of the Milky Way and 0 representing a fully opaque region. The value can slightly exceed unity owing to noise in the SFD98 maps, although it is never below 0.
Extinction coefficients for the SDSS filters have been changed to the values recommended by Schlafly & Finkbeiner (2011) using the Fitzpatrick (1999) extinction curve at R_V = 3.1 and their improved overall calibration of the SFD98 maps. These coefficients are A / E(B-V) = 4.239, 3.303, 2.285, 1.698, 1.263 in \(ugriz\), which are different from those used in SDSS-I,II,III, but are the values used for SDSS-IV/eBOSS target selection.
Extinction coefficients for the DECam filters use the Schlafly & Finkbeiner (2011) values, with \(u\)-band computed using the same formulae and code at airmass 1.3 (Schlafly, priv. comm. decam-data list on 11/13/14). These coefficients are A / E(B-V) = 3.995, 3.214, 2.165, 1.592, 1.211, 1.064 (note that these are slightly different from the coefficients in Schlafly & Finkbeiner 2011).
The coefficients for the four WISE filters are derived from Fitzpatrick (1999), as recommended by Schlafly & Finkbeiner (2011), considered better than either the Cardelli et al. (1989) curves or the newer Fitzpatrick & Massa (2009) NIR curve (which is not vetted beyond 2 microns). These coefficients are A / E(B-V) = 0.184, 0.113, 0.0241, 0.00910.
Ellipticities
The ellipticity, ε, is different from the usual eccentricity, \(e \equiv \sqrt{1 - (b/a)^2}\). In gravitational lensing studies, the ellipticity is taken to be a complex number:
Where ϕ is the position angle with a range of 180°, due to the ellipse's symmetry. Going between \(r, \epsilon_1, \epsilon_2\) and \(r, b/a, \phi\):