## tractor/<AAA>/tractor-<brick>.fits

FITS binary table containing Tractor photometry. Before using these catalogs, note that there are
known issues regarding their content and derivation. In DR4, 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 in DR4.

Name | Type | Units | Description |
---|---|---|---|

release |
int32 | 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 | |

type |
char[4] | Morphological model: "PSF"=stellar, "SIMP"="simple galaxy" = 0.45" round EXP 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, SIMPle, 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 |

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 |

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[7] | nanomaggies | FLUX_W1 in each of up to seven unWISE coadd epochs |

lc_flux_w2 |
float32[7] | nanomaggies | FLUX_W2 in each of up to seven unWISE coadd epochs |

lc_flux_ivar_w1 |
float32[7] | 1/nanomaggies² | Inverse variance of LC_FLUX_W1 |

lc_flux_ivar_w2 |
float32[7] | 1/nanomaggies² | Inverse variance of LC_FLUX_W2 |

lc_nobs_w1 |
int16[7] | NOBS_W1 in each of up to seven unWISE coadd epochs | |

lc_nobs_w2 |
int16[7] | NOBS_W2 in each of up to seven unWISE coadd epochs | |

lc_fracflux_w1 |
float32[7] | FRACFLUX_W1 in each of up to seven unWISE coadd epochs | |

lc_fracflux_w2 |
float32[7] | FRACFLUX_W2 in each of up to seven unWISE coadd epochs | |

lc_rchisq_w1 |
float32[7] | RCHISQ_W1 in each of up to seven unWISE coadd epochs | |

lc_rchisq_w2 |
float32[7] | RCHISQ_W2 in each of up to seven unWISE coadd epochs | |

lc_mjd_w1 |
float32[7] | MJD_W1 in each of up to seven unWISE coadd epochs | |

lc_mjd_w2 |
float32[7] | MJD_W2 in each of up to seven 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"), simple galaxy model ("SIMP"),
de Vaucouleurs model ("DEV"), exponential model ("EXP"), and a composite model ("COMP"), in that order.
The "simple galaxy" model is an exponential galaxy with fixed shape of 0.45″ and zero ellipticity (round)
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. The above 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; http://arxiv.org/abs/1012.4804 ; Table 4) using the Fizpatrick 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.

For DR4, we calculate Galactic extinction for BASS and MzLS as if they were on the DECam filter system (e.g. see DR3).

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. (These are slightly different than the ones in Schlafly & Finkbeiner (2011; http://arxiv.org/abs/1012.4804).)

The coefficients for the four WISE filters are derived from Fitzpatrick (1999), as recommended by Schafly & Finkbeiner, 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 \(r, b/a, \phi\):