Legacy Survey Files

Directory Structures

For Web Access

Top level directory:
https://portal.nersc.gov/cfs/cosmo/data/legacysurvey/dr10/
Top level directory for sweep catalogs:
https://portal.nersc.gov/cfs/cosmo/data/legacysurvey/dr10/south/sweep/

At NERSC (for collaborators)

Top level directory:
/global/cfs/cdirs/cosmo/data/legacysurvey/dr10/
Top level directory for sweep catalogs:
/global/cfs/cdirs/cosmo/data/legacysurvey/dr10/south/sweep/

FITS binary table with the RA, Dec bounds of each geometrical "brick" on the sky. This includes all bricks on the sky, not just the ones in our footprint or with coverage in DR10. For that information, see the next file description.

Column	Type	Description
`BRICKNAME`	char[8]	Name of the brick.
`BRICKID`	int32	A unique integer with 1-to-1 mapping to `brickname`.
`BRICKQ`	int16	A "priority" factor used for processing.
`BRICKROW`	int32	Dec row number.
`BRICKCOL`	int32	Number of the brick within a Dec row.
`RA`	float64	RA of the center of the brick.
`DEC`	float64	Dec of the center of the brick.
`RA1`	float64	Lower RA boundary.
`RA2`	float64	Upper RA boundary.
`DEC1`	float64	Lower Dec boundary.
`DEC2`	float64	Upper Dec boundary.

south/survey-bricks-dr10-south.fits.gz

A FITS binary table with information that summarizes the contents of each brick in DR10.

Column	Type	Description
`brickname`	char[8]	Name of the brick.
`ra`	float64	RA of the center of the brick.
`dec`	float64	Dec of the center of the brick.
`nexp_g`	int16	Median number of exposures in the unique area (i.e. `BRICK_PRIMARY` area) of the brick in \(g\)-band.
`nexp_r`	int16	Median number of exposures in the unique area of the brick in \(r\)-band.
`nexp_i`	int16	Median number of exposures in the unique area of the brick in \(i\)-band.
`nexp_z`	int16	Median number of exposures in the unique area of the brick in \(z\)-band.
`nexphist_g`	int32[11]	Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or > 10 exposures in \(g\).
`nexphist_r`	int32[11]	Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or > 10 exposures in \(r\).
`nexphist_i`	int32[11]	Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or > 10 exposures in \(i\).
`nexphist_z`	int32[11]	Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, or > 10 exposures in \(z\).
`nobjs`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of all types.
`npsf`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `PSF`. See also the larger description.
`nsimp`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `SIMP` (there should be 0 such objects).
`nrex`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `REX`. See also the larger description.
`nexp`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `EXP`. See also the larger description.
`ndev`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `DEV`. See also the larger description.
`ncomp`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `COMP` (there should be 0 such objects).
`nser`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `SER`. See also the larger description.
`ndup`	int32	Total number of `BRICK_PRIMARY` objects in this brick, of type `DUP`. See also the larger description.
`psfsize_g`	float32	Median PSF size, in arcsec, evaluated at the `BRICK_PRIMARY` objects in this brick in \(g\)-band.
`psfsize_r`	float32	Median PSF size, in arcsec, evaluated at the `BRICK_PRIMARY` objects in this brick in \(r\)-band.
`psfsize_i`	float32	Median PSF size, in arcsec, evaluated at the `BRICK_PRIMARY` objects in this brick in \(i\)-band.
`psfsize_z`	float32	Median PSF size, in arcsec, evaluated at the `BRICK_PRIMARY` objects in this brick in \(z\)-band.
`psfdepth_g`	float32	5-sigma PSF detection depth in \(g\)-band (AB mag), using PsfEx PSF model.
`psfdepth_r`	float32	5-sigma PSF detection depth in \(r\)-band (AB mag), using PsfEx PSF model.
`psfdepth_i`	float32	5-sigma PSF detection depth in \(i\)-band (AB mag), using PsfEx PSF model.
`psfdepth_z`	float32	5-sigma PSF detection depth in \(z\)-band (AB mag), using PsfEx PSF model.
`galdepth_g`	float32	5-sigma galaxy (0.45" round exp) detection depth in \(g\)-band (AB) mag.
`galdepth_r`	float32	5-sigma galaxy (0.45" round exp) detection depth in \(r\)-band (AB) mag.
`galdepth_i`	float32	5-sigma galaxy (0.45" round exp) detection depth in \(i\)-band (AB) mag.
`galdepth_z`	float32	5-sigma galaxy (0.45" round exp) detection depth in \(z\)-band (AB) mag.
`ebv`	float32	Median SFD98 dust map E(B-V) extinction, in magnitudes, evaluated at `BRICK_PRIMARY` objects in this brick.
`trans_g`	float32	Median Milky Way dust transparency in \(g\)-band, based on `ebv`. See also `MW_TRANSMISSION_G`.
`trans_r`	float32	Median Milky Way dust transparency in \(r\)-band, based on `ebv`. See also `MW_TRANSMISSION_R`.
`trans_i`	float32	Median Milky Way dust transparency in \(i\)-band, based on `ebv`. See also `MW_TRANSMISSION_I`.
`trans_z`	float32	Median Milky Way dust transparency in \(z\)-band, based on `ebv`. See also `MW_TRANSMISSION_Z`.
`cosky_g`	float32	Estimated sky level in the coadded images (stacks) in \(g\)-band [1].
`cosky_r`	float32	Estimated sky level in the coadded images (stacks) in \(r\)-band.
`cosky_i`	float32	Estimated sky level in the coadded images (stacks) in \(i\)-band.
`cosky_z`	float32	Estimated sky level in the coadded images (stacks) in \(z\)-band.
`ext_g`	float32	Extinction in \(g\)-band.
`ext_r`	float32	Extinction in \(r\)-band.
`ext_i`	float32	Extinction in \(i\)-band.
`ext_z`	float32	Extinction in \(z\)-band.
`wise_nobs`	int16[4]	Number of images that contributed to WISE calculations in each filter (not profile-weighted).
`trans_wise`	float32[4]	Median Milky Way dust transparency in WISE bands, based on `ebv`. See also, e.g., `MW_TRANSMISSION_W1`.
`ext_w1`	float32	Extinction in \(W1\)-band.
`ext_w2`	float32	Extinction in \(W2\)-band.
`ext_w3`	float32	Extinction in \(W3\)-band.
`ext_w4`	float32	Extinction in \(W4\)-band.
`brickid`	int32	A unique integer with 1-to-1 mapping to `brickname`.
`ra1`	float64	Lower RA boundary.
`ra2`	float64	Upper RA boundary.
`dec1`	float64	Lower Dec boundary.
`dec2`	float64	Upper Dec boundary.
`area`	float64	Area of the brick in square degrees.
`survey_primary`	boolean	`True` for northern (southern) bricks that lie in the northern (southern) footprint of the Legacy Surveys.
`in_desi`	boolean	`True` if the brick is in the DESI footprint.

Note that, for the nexphist rows, pixels that are masked by the NOIRLab Community Pipeline as, e.g., cosmic rays or saturation (see, e.g. the ALLMASK/ANYMASK information on the DR10 bitmasks page), do not count toward the number of exposures. More information about the morphological types and MW_TRANSMISSION can be found on the catalogs page.

survey-ccds-decam-dr10.fits.gz

A FITS binary table with almanac information about each individual CCD image for each camera.

This file contains information regarding the photometric and astrometric zero points for each CCD of every image that is part of the DR10 data release. Photometric zero points for each CCD are computed by identifying stars and comparing their instrumental magnitudes to color-selected stars in the PanSTARRS "qz" catalog.

The photometric zeropoints (zpt, ccdzpt, etc) are magnitude-like numbers (e.g. 25.04), and indicate the magnitude of a source that would contribute one count per second to the image. For example, in an image with zeropoint of 25.04 and exposure time of 30 seconds, a source of magnitude 22.5 would contribute \(30 \times 10^{((25.04 - 22.5) / 2.5)} = 311.3\) counts.

Column	Type	Description
`image_filename`	char[65]	Path to FITS image, e.g. "decam/CP/V5.2.2LS/CP20140328/c4d_140329_040642_ooi_r_ls10.fits.fz".
`image_hdu`	int16	FITS HDU number in the `image_filename` file where this image can be found.
`camera`	char[X]	The camera that took this image (X is 7 for "90prime", 6 for "mosaic" and 5 for "decam").
`expnum`	int64	Exposure number, e.g. 348224.
`plver`	char[8]	Community Pipeline (CP) version number.
`procdate`	char[19]	CP processing date.
`plprocid`	char[7]	Unique, time-based, CP processing hash - see the plprocid page for how to convert this to a date.
`ccdname`	char[X]	CCD name, e.g. "N10", "S7" for DECam (X is 4 for 90prime and mosaic CCDs, and 3 for decam).
`object`	char[35]	Name listed in the object tag from the CCD header.
`propid`	char[10]	Proposal ID of the program that took this image, eg "2014B-0404".
`filter`	char[1]	Filter used for observation, e.g. "\(g\)", "\(r\)", "\(i\)", "\(z\)".
`exptime`	float32	Exposure time in seconds, e.g. 30.
`mjd_obs`	float64	Date of observation in MJD (in UTC system), e.g. 56884.99373389.
`airmass`	float32	Airmass of observation (measured at the telescope bore-sight).
`fwhm`	float32	FWHM (in pixels) measured by the CP.
`width`	int16	Width in pixels of this image, e.g. 2046.
`height`	int16	Height in pixels of this image, e.g. 4094.
`ra_bore`	float64	Telescope boresight RA of this exposure (deg).
`dec_bore`	float64	Telescope boresight Dec of this exposure (deg).
`crpix1`	float32	Astrometric header value: X reference pixel.
`crpix2`	float32	Astrometric header value: Y reference pixel.
`crval1`	float64	Astrometric header value: RA of reference pixel.
`crval2`	float64	Astrometric header value: Dec of reference pixel.
`cd1_1`	float32	Astrometric header value: transformation matrix.
`cd1_2`	float32	Astrometric header value: transformation matrix.
`cd2_1`	float32	Astrometric header value: transformation matrix.
`cd2_2`	float32	Astrometric header value: transformation matrix.
`yshift`	boolean	(ignore; it's always `False`).
`ra`	float64	Approximate RA center of this CCD (deg).
`dec`	float64	Approximate Dec center of this CCD (deg).
`skyrms`	float32	Sky rms for the entire image (in counts/second).
`sig1`	float32	Median per-pixel error standard deviation, in nanomaggies.
`ccdzpt`	float32	Zeropoint for the CCD (AB mag).
`zpt`	float32	Median zero point for the entire image (median of all CCDs of the image), e.g. 25.0927.
`ccdraoff`	float32	Median astrometric offset for the CCD <GAIA-Legacy Survey> in arcsec.
`ccddecoff`	float32	Median astrometric offset for the CCD <GAIA-Legacy Survey> in arcsec.
`ccdskycounts`	float32	Mean sky counts level per pixel (AVSKY divided by EXPTIME) in the CP-processed frames measured (with iterative rejection) for each CCD in the image section [500:1500,1500:2500]. DECam exposure data is in electrons. Mosaic and 90prime are in electrons/sec. Sky counts are normalized to maintain a mean level from the original gain-corrected ADU.
`ccdskysb`	float32	Surface brightness (mag/arcsec²) for the sky background.
`ccdrarms`	float32	rms in astrometric offset for the CCD <Gaia-Legacy Survey> in arcsec.
`ccddecrms`	float32	rms in astrometric offset for the CCD <Gaia-Legacy Survey> in arcsec.
`ccdphrms`	float32	Photometric rms for the CCD (in mag).
`phrms`	float32	Median photometric rms across all CCDs in the image (in mag).
`ccdnastrom`	int16	Number of stars (after sigma-clipping) used to compute astrometric correction.
`ccdnphotom`	int16	Number of Gaia+PS1 stars detected with signal-to-noise ratio greater than five.
`ccd_cuts`	int64	Bit mask describing CCD image quality (see the DR10 bitmasks page).
`v4plus`	boolean	`True` if the Community Pipeline (CP) version number (`plver`, above) is >= 4.0.0.

survey-ccds-decam-dr10.kd.fits

As for the survey-ccds-decam-dr10.fits.gz file but limited by the depth of each observation. This file contains the CCDs actually used for the DR10 reductions. Columns are the same as for the survey-ccds-decam-dr10.fits.gz file.

ccds-annotated-decam-dr10.fits.gz

A version of the survey-ccds-decam-dr10.fits.gz file with additional information gathered during calibration pre-processing before running the Tractor reductions.

Includes all of the columns in the survey-ccds-decam-dr10.fits.gz file plus the columns listed below.

Column	Type	Description
`annotated`	boolean	`True` unless there is an error when computing the "annotated" quantities in this row of the file
`good_region`	int16[4]	If only a subset of the CCD images was used, this array of x0,x1,y0,y1 values gives the coordinates that were used, [x0,x1), [y0,y1). -1 for no cut (most CCDs)
`ra0`	float64	RA coordinate of pixel (1,1)...Note that the ordering of the CCD corners is detailed here
`dec0`	float64	Dec coordinate of pixel (1,1)
`ra1`	float64	RA coordinate of pixel (1,H)
`dec1`	float64	Dec coordinate of pixel (1,H)
`ra2`	float64	RA coordinate of pixel (W,H)
`dec2`	float64	Dec coordinate of pixel (W,H)
`ra3`	float64	RA coordinate of pixel (W,1)
`dec3`	float64	Dec coordinate of pixel (W,1)
`dra`	float32	Maximum distance from RA,Dec center to the edge midpoints, in RA
`ddec`	float32	Maximum distance from RA,Dec center to the edge midpoints, in Dec
`ra_center`	float64	RA coordinate of CCD center
`dec_center`	float64	Dec coordinate of CCD center
`meansky`	float32	Our (Tractor) pipeline (not the CP) estimate of the sky level, average over the image, in nanomaggies
`stdsky`	float32	Standard deviation of our sky level, in nanomaggies
`maxsky`	float32	Max of our sky level, in nanomaggies
`minsky`	float32	Min of our sky level, in nanomaggies
`pixscale_mean`	float32	Pixel scale (via sqrt of area of a 10x10 pixel patch evaluated in a 5x5 grid across the image), in arcsec/pixel.
`pixscale_std`	float32	Standard deviation of pixel scale
`pixscale_max`	float32	Max of pixel scale
`pixscale_min`	float32	Min of pixel scale
`psfnorm_mean`	float32	PSF norm = 1/sqrt of N_eff = sqrt(sum(psf_i²)) for normalized PSF pixels i; mean of the PSF model evaluated on a 5x5 grid of points across the image. Point-source detection standard deviation is `sig1 / psfnorm`.
`psfnorm_std`	float32	Standard deviation of PSF norm
`galnorm_mean`	float32	Norm of the PSF model convolved by a 0.45" exponential galaxy.
`galnorm_std`	float32	Standard deviation of galaxy norm.
`psf_mx2`	float32	PSF model second moment in x (pixels²)
`psf_my2`	float32	PSF model second moment in y (pixels²)
`psf_mxy`	float32	PSF model second moment in x-y (pixels²)
`psf_a`	float32	PSF model major axis (pixels)
`psf_b`	float32	PSF model minor axis (pixels)
`psf_theta`	float32	PSF position angle (deg)
`psf_ell`	float32	PSF ellipticity 1 - minor/major
`humidity`	float32	Percent humidity outside
`outtemp`	float32	Outside temperate (degrees C).
`tileid`	int32	tile number, 0 for data from programs other than MzLS or DECaLS
`tilepass`	uint8	tile pass number, 1, 2 or 3, if this was an MzLS or DECaLS observation, or 0 for data from other programs. Set by the observers (the meaning of `tilepass` is on the status page)
`tileebv`	float32	Mean SFD98 E(B-V) extinction in the tile, 0 for data from programs other than BASS, MzLS or DECaLS
`ebv`	float32	SFD98 E(B-V) extinction for CCD center
`decam_extinction`	float32[6]	Extinction for optical filters \(ugrizY\)
`wise_extinction`	float32[4]	Extinction for WISE bands W1,W2,W3,W4
`psfdepth`	float32	5-sigma PSF detection depth in AB mag, using PsfEx PSF model
`galdepth`	float32	5-sigma galaxy (0.45" round exp) detection depth in AB mag
`gausspsfdepth`	float32	5-sigma PSF detection depth in AB mag, using Gaussian PSF approximation (using `seeing` value)
`gaussgaldepth`	float32	5-sigma galaxy detection depth in AB mag, using Gaussian PSF approximation

south/dr10-south-depth.fits.gz

A concatenation of the depth histograms for each brick, from the coadd/*/*/*-depth.fits tables. HDU1 contains histograms that describe the number of pixels in each brick with a 5-sigma AB depth in the given magnitude bin. HDU2 contains the bin edges of the histograms.

HDU1

Column	Type	Description
`counts_ptsrc_g`	int32[50]	Histogram of pixels for point source depth in \(g\) band
`counts_gal_g`	int32[50]	Histogram of pixels for canonical galaxy depth in \(g\) band
`counts_ptsrc_r`	int32[50]	Histogram of pixels for point source depth in \(r\) band
`counts_gal_r`	int32[50]	Histogram of pixels for canonical galaxy depth in \(r\) band
`counts_ptsrc_i`	int32[50]	Histogram of pixels for point source depth in \(i\) band
`counts_gal_i`	int32[50]	Histogram of pixels for canonical galaxy depth in \(i\) band
`counts_ptsrc_z`	int32[50]	Histogram of pixels for point source depth in \(z\) band
`counts_gal_z`	int32[50]	Histogram of pixels for canonical galaxy depth in \(z\) band
`brickname`	char[8]	Name of the brick

HDU2

Column	Type	Description
`depthlo`	float32	Lower bin edge for each histogram in HDU1 (5-sigma AB depth)
`depthhi`	float32	Upper bin edge for each histogram in HDU1 (5-sigma AB depth)

south/dr10-south-depth-summary.fits.gz

A summary of the depth histogram for DR10. FITS table with the following columns:

Column	Type	Description
`depthlo`	float32	Lower limit of the depth bin
`depthhi`	float32	Upper limit of the depth bin
`counts_ptsrc_g`	int64	Number of pixels in histogram for point source depth in \(g\) band
`counts_gal_g`	int64	Number of pixels in histogram for canonical galaxy depth in \(g\) band
`counts_ptsrc_r`	int64	Number of pixels in histogram for point source depth in \(r\) band
`counts_gal_r`	int64	Number of pixels in histogram for canonical galaxy depth in \(r\) band
`counts_ptsrc_i`	int64	Number of pixels in histogram for point source depth in \(i\) band
`counts_gal_i`	int64	Number of pixels in histogram for canonical galaxy depth in \(i\) band
`counts_ptsrc_z`	int64	Number of pixels in histogram for point source depth in \(z\) band
`counts_gal_z`	int64	Number of pixels in histogram for canonical galaxy depth in \(z\) band

The depth histogram runs from magnitude of 20.1 to 24.9 in steps of 0.1 mag. The first and last bins are "catch-all" bins: 0 to 20.1 and 24.9 to 100, respectively. The histograms count the number of pixels in each brick's unique area with the given depth. These numbers can be turned into values in square degrees using the brick pixel area of 0.262 arcseconds square. These depth estimates take into account the small-scale masking (cosmic rays, edges, saturated pixels) and detailed PSF model.

Random Catalogs (`randoms/*`)

randoms-1-*.fits

Twenty files of random points sampled across the CCDs that comprise the geometry of DR9 (see Myers et al. 2023). Random locations were generated across the footprint at a density of 2,500 per square degree and meta-information about the survey was extracted from pixels at each random location from files in the coadd directory (see below, e.g. coadd/*/*/*-depth-<filter>.fits.fz, coadd/*/*/*-galdepth-<filter>.fits.fz, coadd/*/*/*-nexp-<filter>.fits.fz, coadd/*/*/*-maskbits.fits.fz, coadd/*/*/*-invvar-<filter>.fits.fz). The order of the points within each file is also random (meaning that randomness is retained if just the first N rows of the file are read). Each file contains the following columns:

Column	Type	Description
`RELEASE`	int16	Integer denoting the camera and filter set used, which will be unique for a given processing run of the data (RELEASE is documented here)
`BRICKID`	int32	A unique Brick ID (in the range [1, 662174])
`BRICKNAME`	char[8]	Name of the brick
`BRICK_OBJID`	int32	Random catalog object number enumerate by increasing `RA` within each brick; a unique identifier hash is `RELEASE,BRICKID,BRICK_OBJID`
`RA`	float64	Right ascension at equinox J2000
`DEC`	float64	Declination at equinox J2000
`NOBS_G`	int16	Number of images that contribute to the central pixel in the \(g\) filter for this location (not profile-weighted)
`NOBS_R`	int16	Number of images that contribute to the central pixel in the \(r\) filter for this location (not profile-weighted)
`NOBS_I`	int16	Number of images that contribute to the central pixel in the \(i\) filter for this location (not profile-weighted)
`NOBS_Z`	int16	Number of images that contribute to the central pixel in the \(z\) filter for this location (not profile-weighted)
`PSFDEPTH_G`	float32	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	For a \(5\sigma\) point source detection limit in \(r\), \(5/\sqrt(\mathrm{PSFDEPTH\_R})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_R})) - 9]\) gives corresponding magnitude
`PSFDEPTH_I`	float32	For a \(5\sigma\) point source detection limit in \(i\), \(5/\sqrt(\mathrm{PSFDEPTH\_I})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_I})) - 9]\) gives corresponding magnitude
`PSFDEPTH_Z`	float32	For a \(5\sigma\) point source detection limit in \(z\), \(5/\sqrt(\mathrm{PSFDEPTH\_Z})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_Z})) - 9]\) gives corresponding magnitude
`GALDEPTH_G`	float32	As for `PSFDEPTH_G` but for a galaxy (0.45" exp, round) detection sensitivity
`GALDEPTH_R`	float32	As for `PSFDEPTH_R` but for a galaxy (0.45" exp, round) detection sensitivity
`GALDEPTH_I`	float32	As for `PSFDEPTH_I` but for a galaxy (0.45" exp, round) detection sensitivity
`GALDEPTH_Z`	float32	As for `PSFDEPTH_Z` but for a galaxy (0.45" exp, round) detection sensitivity
`PSFDEPTH_W1`	float32	As for `PSFDEPTH_G` (and also on the AB system) but for WISE W1
`PSFDEPTH_W2`	float32	As for `PSFDEPTH_G` (and also on the AB system) but for WISE W2
`PSFSIZE_G`	float32	Weighted average PSF FWHM in arcsec in the \(g\) band
`PSFSIZE_R`	float32	Weighted average PSF FWHM in arcsec in the \(r\) band
`PSFSIZE_I`	float32	Weighted average PSF FWHM in arcsec in the \(i\) band
`PSFSIZE_Z`	float32	Weighted average PSF FWHM in arcsec in the \(z\) band
`APFLUX_G`	float32	Total flux in nanomaggies extracted in a 0.75 arcsec radius in the \(g\) band at this location
`APFLUX_R`	float32	Total flux in nanomaggies extracted in a 0.75 arcsec radius in the \(r\) band at this location
`APFLUX_I`	float32	Total flux in nanomaggies extracted in a 0.75 arcsec radius in the \(i\) band at this location
`APFLUX_Z`	float32	Total flux in nanomaggies extracted in a 0.75 arcsec radius in the \(z\) band at this location
`APFLUX_IVAR_G`	float32	Inverse variance of `APFLUX_G`
`APFLUX_IVAR_R`	float32	Inverse variance of `APFLUX_R`
`APFLUX_IVAR_I`	float32	Inverse variance of `APFLUX_I`
`APFLUX_IVAR_Z`	float32	Inverse variance of `APFLUX_Z`
`MASKBITS`	int32	Bitwise mask for optical data in the `coadd///maskbits` maps (see the DR10 bitmasks page)
`WISEMASK_W1`	uint8	Bitwise mask for WISE W1 data in the `coadd///maskbits` maps (see the DR10 bitmasks page)
`WISEMASK_W2`	uint8	Bitwise mask for WISE W2 data in the `coadd///maskbits` maps (see the DR10 bitmasks page)
`EBV`	float32	Galactic extinction E(B-V) reddening from SFD98
`PHOTSYS`	char[1]	'N' for an MzLS/BASS location, 'S' for a DECaLS (or DECam) location
`HPXPIXEL`	int64	HEALPixel containing this location at NSIDE=64 in the NESTED scheme
`TARGETID`	int64	See the DESI data model (added to facilitate running randoms through the DESI fiberassign code)
`DESI_TARGET`	int64	See the DESI data model; set to 4, appropriate to a QSO, the highest-priority DESI dark-time target (added to facilitate running randoms through the DESI fiberassign code)
`BGS_TARGET`	int64	See the DESI data model; set to zero (added to facilitate running randoms through the DESI fiberassign code)
`MWS_TARGET`	int64	See the DESI data model; set to zero (added to facilitate running randoms through the DESI fiberassign code)
`SUBPRIORITY`	int64	See the DESI data model (added to facilitate running randoms through the DESI fiberassign code)
`OBSCONDITIONS`	int32	See the DESI data model; set to 1023, which corresponds to all possible observing conditions (added to facilitate running randoms through the DESI fiberassign code)
`PRIORITY_INIT`	int64	See the DESI data model; set to 3400, appropriate to a QSO, the highest-priority DESI dark-time target (added to facilitate running randoms through the DESI fiberassign code)
`NUMOBS_INIT`	int64	See the DESI data model; set to 4, appropriate to a QSO, the highest-priority DESI dark-time target (added to facilitate running randoms through the DESI fiberassign code)
`SCND_TARGET`	int64	See the DESI data model; set to 0 (added to facilitate running randoms through the DESI fiberassign code)
`NUMOBS_MORE`	int64	See the DESI data model; set to 4, appropriate to a QSO, the highest-priority DESI dark-time target (added to facilitate running randoms through the DESI fiberassign code)
`NUMOBS`	int64	See the DESI data model; set to 0 (added to facilitate running randoms through the DESI fiberassign code)
`Z`	float64	See the DESI data model; set to -1.0 (added to facilitate running randoms through the DESI fiberassign code)
`ZWARN`	int64	See the DESI data model; set to -1 (added to facilitate running randoms through the DESI fiberassign code)
`ZTILEID`	int32	See the DESI data model; set to -1 (added to facilitate running randoms through the DESI fiberassign code)
`Z_QN`	float64	See the DESI data model; set to -1 (added to facilitate running randoms through the DESI fiberassign code)
`IS_QSO_QN`	int16	See the DESI data model; set to -1 (added to facilitate running randoms through the DESI fiberassign code)
`DELTACHI2`	float64	See the DESI data model; set to -1 (added to facilitate running randoms through the DESI fiberassign code)
`TARGET_STATE`	char[30]	See the DESI data model; set to "QSO\|UNOBS", denoting an unobserved QSO (added to facilitate running randoms through the DESI fiberassign code)
`TIMESTAMP`	char[25]	See the DESI data model; time at which this random was processed (added to facilitate running randoms through the DESI fiberassign code)
`VERSION`	char[14]	See the DESI data model; version of the `desitarget` code used to process this random (added to facilitate running randoms through the DESI fiberassign code)
`PRIORITY`	int64	See the DESI data model; set to 3400, appropriate to a QSO, the highest-priority DESI dark-time target (added to facilitate running randoms through the DESI fiberassign code)

The version of the desitarget code used to generate the random catalogs (2.6.0) can be extracted from the VERSION column. The code is available on GitHub (see also here). The northern and southern imaging footprints overlap, so, randoms are resolved by the desitarget code at a particular declination and by the Galactic plane. The result is that randoms with locations at Dec \(\geq\) 32.375° and that are north of the Galactic Plane are only included in this file if they have pixels in BASS/MzLS (PHOTSYS set to "N"), and randoms with locations at Dec < 32.375° or that are south of the Galactic Plane are only included in this file if they have pixels observed with DECam (PHOTSYS set to "S").

Work which uses any of the random catalogs should cite Myers et al. (2023).

randoms-outside-1-*.fits

Twenty files of random points in bricks that do not contain an observation in DR10 (i.e. that are "outside" of the DR10 footprint). The columns in this file are simplified compared to the other random catalogs as most of the entries in the additional columns would be zeros. As with the other random catalogs, points were generated at a density of 2,500 per square degree and the order of the points within the file is also randomized. Contains the following columns:

Column	Type	Description
`BRICKID`	int32	A unique Brick ID (in the range [1, 662174])
`BRICKNAME`	char[8]	Name of the brick
`RA`	float64	Right ascension at equinox J2000
`DEC`	float64	Declination at equinox J2000
`NOBS_G`	int16	Always zero in this file.
`NOBS_R`	int16	Always zero in this file.
`NOBS_I`	int16	Always zero in this file.
`NOBS_Z`	int16	Always zero in this file.
`EBV`	float32	Galactic extinction E(B-V) reddening from SFD98

randoms-allsky-1-*.fits

The (randomly shuffled) combination of each of the randoms-1-X.fits and randoms-outside-1-X.fits files (where X = 0, 1, 2, 3, ... 18, 19). This creates twenty "all-sky" random catalogs (at a density of 2,500 locations per square degree) where each brick is either populated with observations from the Legacy Surveys, or zeros. Contains a subset of the columns from the randoms-1-X.fits files.

survey-bricks-dr10-randoms-2.6.0.fits

A similar file to the survey-bricks.fits.gz file, but with extra columns to help interpret the random catalogs. Contains the same columns as the survey-bricks.fits.gz file, plus the additional columns:

Column	Type	Description
`PHOTSYS`	char[1]	`"N"`, `"S"` or `" "` for bricks resolved to be "officially" in the north, south, or outside of the footprint, respectively.
`AREA_PER_BRICK`	float64	The area of the brick in square degrees.

south/randoms/randoms-south-1-*.fits

As for the corresponding randoms-1-*.fits file, but without resolving randoms using the desitarget code. In other words, this file contains all randoms for dr10, regardless of whether the brick is "officially" in the south region.

External Match Files (`south/external/*`)

The Legacy Survey photometric catalogs have been matched to a range of external spectroscopic files from the SDSS. These external spectroscopic files can be accessed on the NERSC computers (for collaborators) at:

/global/cfs/cdirs/sdss/data/sdss

The resulting catalogs, which are listed below, can be accessed through the web at:

https://portal.nersc.gov/cfs/cosmo/data/legacysurvey/dr10/south/external/

Or on the NERSC computers at:

/global/cfs/cdirs/cosmo/data/legacysurvey/dr10/south/external/

Each row of each external-match file contains the full record of the nearest object in our Tractored survey imaging catalogs, matched at a radius of 1.5 arcsec. The structure of the imaging catalog files is documented on the catalogs page. If no match is found, then OBJID is set to -1.

In addition to the columns from the Tractor catalogs, we have added columns from the SDSS files that can be used to track objects uniquely. These are typically some combination of PLATE, FIBER, MJD (or SMJD) and, in some cases, RERUN.

In previous Data Releases, if a source was duplicated in the SDSS spectroscopic files, only one of the duplicates was matched to a Legacy Surveys photometric object. Continuing the approach we started with DR9, we now match all duplicates in the SDSS spectroscopic files. The result is that all sources in the SDSS spectroscopic files should have information from the Legacy Surveys imaging if they match with any Legacy Surveys BRICK_PRIMARY photometric object.

survey-dr(10|10.1)-south-specObj-dr16.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR16 spectrosopic pipeline file such that the photometric parameters in row "N" of survey-dr10-south-specObj-dr16.fits match the spectroscopic parameters in row "N" of specObj-dr16.fits. The spectroscopic file is documented in the SDSS DR16 data model for specObj-dr16.fits.

survey-dr(10|10.1)-south-dr16Q-v4.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR16 visually inspected quasar catalog (Lyke et al. 2020) such that the photometric parameters in row "N" of survey-dr10-south-dr16Q-v4.fits match the spectroscopic parameters in row "N" of DR16Q_v4.fits. The spectroscopic file is documented in the SDSS DR14 data model for DR16Q_v4.fits.

survey-dr(10|10.1)-south-superset-dr16Q-v3.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the superset of all SDSS DR16 spectroscopically confirmed objects that were visually inspected as possible quasars (Lyke et al. 2020) such that the photometric parameters in row "N" of survey-dr10-south-superset-dr16Q-v3.fits match the spectroscopic parameters in row "N" of DR16Q_Superset_v3.fits. The spectroscopic file is documented in the SDSS DR16 data model for DR16Q_Superset_v3.fits.

survey-dr(10|10.1)-south-dr12Q.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR12 visually inspected quasar catalog (Paris et al. 2017) such that the photometric parameters in row "N" of survey-dr10-south-dr12Q.fits match the spectroscopic parameters in row "N" of DR12Q.fits. The spectroscopic file is documented in the SDSS DR12 data model for DR12Q.fits.

survey-dr(10|10.1)-south-superset-dr12Q.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the superset of all SDSS DR12 spectroscopically confirmed objects that were visually inspected as possible quasars (Paris et al. 2017) such that the photometric parameters in row "N" of survey-dr10-south-superset-dr12Q.fits match the spectroscopic parameters in row "N" of Superset_DR12Q.fits. The spectroscopic file is documented in the SDSS DR12 data model for Superset_DR12Q.fits.

survey-dr(10|10.1)-south-dr7Q.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR7 visually inspected quasar catalog (Schneider et al. 2010) such that the photometric parameters in row "N" of survey-dr10-south-dr7Q.fits match the spectroscopic parameters in row "N" of DR7qso.fit. The spectroscopic file is documented on the DR7 quasar catalog description page.

Tractor Catalogs (`south/tractor/*`)

In the file listings outlined below:

brick names (<brick>) have the format <AAAa>c<BBB> where A, a and B are digits and c is either the letter m or p (e.g. 1126p222). The names are derived from the (RA, Dec) center of the brick. The first four digits are \(int(RA \times 10)\), followed by p to denote positive Dec or m to denote negative Dec ("plus"/"minus"), followed by three digits of \(int(Dec \times 10)\). For example the case 1126p222 corresponds to (RA, Dec) = (112.6°, +22.2°).
<brickmin> and <brickmax> denote the corners of a rectangle in (RA, Dec). Explicitly, <brickmin> has the format <AAA>c<BBB> where <AAA> denotes three digits of the minimum \(int(RA)\) in degrees, <BBB> denotes three digits of the minimum \(int(Dec)\) in degrees, and c uses the p/m ("plus"/"minus") format outlined in the previous bullet point. The convention is similar for <brickmax> and the maximum RA and Dec. For example 000m010-010m005 would correspond to a survey area limited by \(0^\circ \leq RA < 10^\circ\) and \(-10^\circ \leq Dec < -5^\circ\).
sub-directories are listed by the RA of the brick center, and sub-directory names (<AAA>) correspond to RA. For example 002 corresponds to brick centers between an RA of 2° and an RA of 3°.
<filter> denotes the \(g\), \(r\), \(i\) or \(z\) band, using the corresponding letter.

Note that it is not possible to go from a brick name back to an exact (RA, Dec) center (the bricks are not on 0.1° grid lines). The exact brick center for a given brick name can be derived from columns in the survey-bricks.fits.gz file (i.e. brickname, ra, dec).

<AAA>/tractor-<brick>.fits

FITS binary table containing Tractor photometry, documented on the catalogs page.

Users interested in database access to the Tractor catalogs can use the NOIRLab Astro Data Lab [2].

Sweep Catalogs (`south/sweep/*`)

10.[0-1]/sweep-<brickmin>-<brickmax>.fits

The sweeps are light-weight FITS binary tables (containing a subset of the most commonly used Tractor measurements) of all the Tractor catalogs for which BRICK_PRIMARY==T in rectangles of RA, Dec.

Name	Type	Units	Description
`RELEASE`	int16		Integer denoting the camera and filter set used, which will be unique for a given processing run of the data (RELEASE is documented here)
`BRICKID`	int32		A unique Brick ID (in the range [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 `RELEASE,BRICKID,OBJID`; `OBJID` spans [0,N-1] and is contiguously enumerated within each blob
`TYPE`	char[3]		Morphological model: "PSF"=stellar, "REX"="round exponential galaxy" = round EXP galaxy with a variable radius, "EXP"=exponential, "DEV"=deVauc, "SER"=Sersic, "DUP"==Gaia source fit by different model. See also the larger description.
`RA`	float64	deg	Right ascension at equinox J2000
`DEC`	float64	deg	Declination at equinox 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
`DCHISQ`	float32[5]		Difference in χ² between successively more-complex model fits: PSF, REX, DEV, EXP, SER. The difference is versus no source.
`EBV`	float32	mag	Galactic extinction E(B-V) reddening from SFD98, used to compute `MW_TRANSMISSION`
`FLUX_G`	float32	nanomaggy	Model flux in \(g\)
`FLUX_R`	float32	nanomaggy	Model flux in \(r\)
`FLUX_I`	float32	nanomaggy	Model flux in \(i\)
`FLUX_Z`	float32	nanomaggy	Model flux in \(z\)
`FLUX_W1`	float32	nanomaggy	WISE model flux in \(W1\) (AB system)
`FLUX_W2`	float32	nanomaggy	WISE model flux in \(W2\) (AB)
`FLUX_W3`	float32	nanomaggy	WISE model flux in \(W3\) (AB)
`FLUX_W4`	float32	nanomaggy	WISE model flux in \(W4\) (AB)
`FLUX_IVAR_G`	float32	1/nanomaggy²	Inverse variance of `FLUX_G`
`FLUX_IVAR_R`	float32	1/nanomaggy²	Inverse variance of `FLUX_R`
`FLUX_IVAR_I`	float32	1/nanomaggy²	Inverse variance of `FLUX_I`
`FLUX_IVAR_Z`	float32	1/nanomaggy²	Inverse variance of `FLUX_Z`
`FLUX_IVAR_W1`	float32	1/nanomaggy²	Inverse variance of `FLUX_W1` (AB system)
`FLUX_IVAR_W2`	float32	1/nanomaggy²	Inverse variance of `FLUX_W2` (AB)
`FLUX_IVAR_W3`	float32	1/nanomaggy²	Inverse variance of `FLUX_W3` (AB)
`FLUX_IVAR_W4`	float32	1/nanomaggy²	Inverse variance of `FLUX_W4` (AB)
`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_R`	float32		Galactic transmission in \(i\) 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_I`	int16		Number of images that contribute to the central pixel in \(i\): 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_I`	float32		Profile-weighted χ² of model fit normalized by the number of pixels in \(i\)
`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_I`	float32		Profile-weighted fraction of the flux from other sources divided by the total flux in \(i\) (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_I`	float32		Profile-weighted fraction of pixels masked from all observations of this object in \(i\), 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_I`	float32		Fraction of a source's flux within the blob in \(i\), 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 \(g\) (see the DR10 bitmasks page)
`ANYMASK_R`	int16		Bitwise mask set if the central pixel from any image satisfies each condition in \(r\) (see the DR10 bitmasks page)
`ANYMASK_I`	int16		Bitwise mask set if the central pixel from any image satisfies each condition in \(i\) (see the DR10 bitmasks page)
`ANYMASK_Z`	int16		Bitwise mask set if the central pixel from any image satisfies each condition in \(z\) (see the DR10 bitmasks page)
`ALLMASK_G`	int16		Bitwise mask set if the central pixel from all images satisfy each condition in \(g\) (see the DR10 bitmasks page)
`ALLMASK_R`	int16		Bitwise mask set if the central pixel from all images satisfy each condition in \(r\) (see the DR10 bitmasks page)
`ALLMASK_I`	int16		Bitwise mask set if the central pixel from all images satisfy each condition in \(i\) (see the DR10 bitmasks page)
`ALLMASK_Z`	int16		Bitwise mask set if the central pixel from all images satisfy each condition in \(z\) (see the DR10 bitmasks page)
`WISEMASK_W1`	uint8		W1 bitmask as cataloged on the DR10 bitmasks page
`WISEMASK_W2`	uint8		W2 bitmask as cataloged on the DR10 bitmasks page
`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_I`	float32	arcsec	Weighted average PSF FWHM in the \(i\) band
`PSFSIZE_Z`	float32	arcsec	Weighted average PSF FWHM in the \(z\) band
`PSFDEPTH_G`	float32	1/nanomaggy²	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/nanomaggy²	For a \(5\sigma\) point source detection limit in \(r\), \(5/\sqrt(\mathrm{PSFDEPTH\_R})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_R})) - 9]\) gives corresponding magnitude
`PSFDEPTH_I`	float32	1/nanomaggy²	For a \(5\sigma\) point source detection limit in \(i\), \(5/\sqrt(\mathrm{PSFDEPTH\_I})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_I})) - 9]\) gives corresponding magnitude
`PSFDEPTH_Z`	float32	1/nanomaggy²	For a \(5\sigma\) point source detection limit in \(z\), \(5/\sqrt(\mathrm{PSFDEPTH\_Z})\) gives flux in nanomaggies and \(-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_Z})) - 9]\) gives corresponding magnitude
`GALDEPTH_G`	float32	1/nanomaggy²	As for `PSFDEPTH_G` but for a galaxy (0.45" exp, round) detection sensitivity
`GALDEPTH_R`	float32	1/nanomaggy²	As for `PSFDEPTH_R` but for a galaxy (0.45" exp, round) detection sensitivity
`GALDEPTH_I`	float32	1/nanomaggy²	As for `PSFDEPTH_I` but for a galaxy (0.45" exp, round) detection sensitivity
`GALDEPTH_Z`	float32	1/nanomaggy²	As for `PSFDEPTH_Z` but for a galaxy (0.45" exp, round) detection sensitivity
`PSFDEPTH_W1`	float32	1/nanomaggy²	As for `PSFDEPTH_G` (and also on the AB system) but for WISE W1
`PSFDEPTH_W2`	float32	1/nanomaggy²	As for `PSFDEPTH_G` (and also on the AB system) but for WISE W2
`WISE_COADD_ID`	char[8]		unWISE coadd file name for the center of each object
`SHAPE_R`	float32	arcsec	Half-light radius of galaxy model for galaxy type `TYPE` (>0)
`SHAPE_R_IVAR`	float32	1/arcsec²	Inverse variance of `SHAPE_R`
`SHAPE_E1`	float32		Ellipticity component 1 of galaxy model for galaxy type `TYPE`
`SHAPE_E1_IVAR`	float32		Inverse variance of `SHAPE_E1`
`SHAPE_E2`	float32		Ellipticity component 2 of galaxy model for galaxy type `TYPE`
`SHAPE_E2_IVAR`	float32		Inverse variance of `SHAPE_E2`
`FIBERFLUX_G`	float32	nanomaggy	Predicted \(g\)-band flux within a fiber of diameter 1.5 arcsec from this object in 1 arcsec Gaussian seeing
`FIBERFLUX_R`	float32	nanomaggy	Predicted \(r\)-band flux within a fiber of diameter 1.5 arcsec from this object in 1 arcsec Gaussian seeing
`FIBERFLUX_I`	float32	nanomaggy	Predicted \(i\)-band flux within a fiber of diameter 1.5 arcsec from this object in 1 arcsec Gaussian seeing
`FIBERFLUX_Z`	float32	nanomaggy	Predicted \(z\)-band flux within a fiber of diameter 1.5 arcsec from this object in 1 arcsec Gaussian seeing
`FIBERTOTFLUX_G`	float32	nanomaggy	Predicted \(g\)-band flux within a fiber of diameter 1.5 arcsec from all sources at this location in 1 arcsec Gaussian seeing
`FIBERTOTFLUX_R`	float32	nanomaggy	Predicted \(r\)-band flux within a fiber of diameter 1.5 arcsec from all sources at this location in 1 arcsec Gaussian seeing
`FIBERTOTFLUX_I`	float32	nanomaggy	Predicted \(i\)-band flux within a fiber of diameter 1.5 arcsec from all sources at this location in 1 arcsec Gaussian seeing
`FIBERTOTFLUX_Z`	float32	nanomaggy	Predicted \(z\)-band flux within a fiber of diameter 1.5 arcsec from all sources at this location in 1 arcsec Gaussian seeing
`REF_CAT`	char[2]		Reference catalog source for this star: "T2" for Tycho-2, "GE" for Gaia EDR3, "L3" for the SGA, empty otherwise
`REF_ID`	int64		Reference catalog identifier for this star; Tyc11,000,000+Tyc210+Tyc3 for Tycho-2; "sourceid" for Gaia EDR3 and SGA
`REF_EPOCH`	float32	yr	Reference catalog reference epoch (eg, 2016.0 for Gaia EDR3)
`GAIA_PHOT_G_MEAN_MAG`	float32	mag	Gaia EDR3 G band magnitude
`GAIA_PHOT_G_MEAN_FLUX_OVER_ERROR`	float32		Gaia EDR3 G band signal-to-noise
`GAIA_PHOT_BP_MEAN_MAG`	float32	mag	Gaia EDR3 BP magnitude
`GAIA_PHOT_BP_MEAN_FLUX_OVER_ERROR`	float32		Gaia EDR3 BP signal-to-noise
`GAIA_PHOT_RP_MEAN_MAG`	float32	mag	Gaia EDR3 RP magnitude
`GAIA_PHOT_RP_MEAN_FLUX_OVER_ERROR`	float32		Gaia EDR3 RP signal-to-noise
`GAIA_ASTROMETRIC_EXCESS_NOISE`	float32		Gaia EDR3 astrometric excess noise
`GAIA_DUPLICATED_SOURCE`	boolean		Gaia EDR3 duplicated source flag (1/0 for True/False)
`GAIA_PHOT_BP_RP_EXCESS_FACTOR`	float32		Gaia EDR3 BP/RP excess factor
`GAIA_ASTROMETRIC_SIGMA5D_MAX`	float32	mas	Gaia EDR3 longest semi-major axis of the 5-d error ellipsoid
`GAIA_ASTROMETRIC_PARAMS_SOLVED`	uint8		Which astrometric parameters were estimated for a Gaia EDR3 source
`PARALLAX`	float32	mas	Reference catalog parallax
`PARALLAX_IVAR`	float32	1/mas²	Reference catalog inverse-variance on `PARALLAX`
`PMRA`	float32	mas/yr	Reference catalog proper motion in RA direction (\(\mu_\alpha^*\equiv\mu_\alpha\cos\delta\)) in the ICRS at `REF_EPOCH`
`PMRA_IVAR`	float32	1/(mas/yr)²	Reference catalog inverse-variance on `PMRA`
`PMDEC`	float32	mas/yr	Reference catalog proper motion in Dec direction (\(\mu_\delta\)) in the ICRS at `REF_EPOCH`
`PMDEC_IVAR`	float32	1/(mas/yr)²	Reference catalog inverse-variance on `PMDEC`
`MASKBITS`	int32		Bitwise mask indicating that an object touches a pixel in the `coadd///maskbits` maps (see the DR10 bitmasks page)
`FITBITS`	int16		Bitwise mask detailing properties of how a source was fit (see the DR10 bitmasks page)
`SERSIC`	float32		Power-law index for the Sersic profile model (`TYPE="SER"`)
`SERSIC_IVAR`	float32		Inverse variance of `SERSIC`

Light Curve sweeps (10.[0-1]-lightcurves/sweep-<brickmin>-<brickmax>-lc.fits)

The "light curve" sweeps files contain values from the Tractor catalogs that relate to multi-epoch WISE data, which are

Name	Type	Units	Description
`RELEASE`	int16		Integer denoting the camera and filter set used, which will be unique for a given processing run of the data (RELEASE is documented here)
`BRICKID`	int32		A unique Brick ID (in the range [1, 662174])
`OBJID`	int32		Catalog object number within this brick; a unique identifier hash is `RELEASE,BRICKID,OBJID`; `OBJID` spans [0,N-1] and is contiguously enumerated within each blob
`LC_FLUX_W1`	float32[17]	nanomaggy	`FLUX_W1` in each of up to seventeen unWISE coadd epochs (AB system; defaults to zero for unused entries)
`LC_FLUX_W2`	float32[17]	nanomaggy	`FLUX_W2` in each of up to seventeen unWISE coadd epochs (AB; defaults to zero for unused entries)
`LC_FLUX_IVAR_W1`	float32[17]	1/nanomaggy²	Inverse variance of `LC_FLUX_W1` (AB system; defaults to zero for unused entries)
`LC_FLUX_IVAR_W2`	float32[17]	1/nanomaggy²	Inverse variance of `LC_FLUX_W2` (AB; defaults to zero for unused entries)
`LC_NOBS_W1`	int16[17]		`NOBS_W1` in each of up to seventeen unWISE coadd epochs
`LC_NOBS_W2`	int16[17]		`NOBS_W2` in each of up to seventeen unWISE coadd epochs
`LC_MJD_W1`	float64[17]		`MJD_W1` in each of up to seventeen unWISE coadd epochs (defaults to zero for unused entries)
`LC_MJD_W2`	float64[17]		`MJD_W2` in each of up to seventeen unWISE coadd epochs (defaults to zero for unused entries)
`LC_FRACFLUX_W1`	float32[17]		`FRACFLUX_W1` in each of up to seventeen unWISE coadd epochs (defaults to zero for unused entries)
`LC_FRACFLUX_W2`	float32[17]		`FRACFLUX_W2` in each of up to seventeen unWISE coadd epochs (defaults to zero for unused entries)
`LC_RCHISQ_W1`	float32[17]		`RCHISQ_W1` in each of up to seventeen unWISE coadd epochs (defaults to zero for unused entries)
`LC_RCHISQ_W2`	float32[17]		`RCHISQ_W2` in each of up to seventeen unWISE coadd epochs (defaults to zero for unused entries)
`LC_EPOCH_INDEX_W1`	int16[17]		Index number of unWISE epoch for W1 (defaults to -1 for unused entries)
`LC_EPOCH_INDEX_W2`	int16[17]		Index number of unWISE epoch for W2 (defaults to -1 for unused entries)

The light curve sweeps files are row-by-row-parallel to the standard sweeps files (i.e. the entries in each row of the light curve sweeps files correspond to the entries in each row of the standard sweeps files, which can be verified using RELEASE, BRICKID and OBJID).

Extra sweeps (10.[0-1]-extra/sweep-<brickmin>-<brickmax>-ex.fits)

The "extra" sweeps files contain all columns from the Tractor catalogs that are not otherwise in the standard sweeps files or the "light curve" sweep files. See the Tractor catalogs for a description of the columns in these files. The extra sweeps files are row-by-row-parallel to the standard sweeps files (i.e. the entries in each row of the extra sweeps files correspond to the entries in each row of the standard sweeps files, which can be verified using RELEASE, BRICKID and OBJID).

Photo-z sweeps (10.1-photo-z/sweep-<brickmin>-<brickmax>-pz.fits)

The photometric redshift (photo-z) sweeps catalogs are row-by-row-matched to the DR10.1 sweep catalogs as described above for the other types of sweeps files.

The photometric redshifts are computed using a random forest algorithm. Details of the photo-z training and performance are similar to those found in Zhou et al. (2023). We include two sets of photo-zs as part of DR10.1. Both sets include WISE W1 and W2 fluxes, but one includes just \(grz\) fluxes in the optical and one is extended to include \(i\)-band fluxes. Columns in the catalogs that additionally use \(i\)-band can be identified by _I in the column name. For computing the photo-zs, we require at least one exposure in each \(griz\) band of interest. For example, for the \(grz\)-based photo-zs we require at least one exposure in each of the \(g\), \(r\) and \(z\) bands (NOBS_G,R,Z>1). For objects that do not meet the NOBS cut, the photo-z values are filled with -99.

Although we provide photo-zs for all objects that meet the NOBS cut, the brightest objects have the most reliable photo-zs. As a rule of thumb, objects brighter than \(z\)-band magnitude of 21 are mostly reliable, whereas fainter objects are increasingly unreliable with increasingly large systematic offsets. Plots of the overall performance of the photometric redshifts compared to a range of spectroscopic surveys are available for both the photo-zs that do not include i-band and those that include i-band. We also provide a table summarizing the relative performance of the photo-zs with and without i-band that can be compared to Table 7 of Zhou et al. (2023).

The photo-z catalogs do not provide information on star-galaxy separation. We do not attempt to identify stars, which are excluded from the photo-z training data. To perform star-galaxy separation, one can use the morphological TYPE and/or the photometry (e.g., an optical-WISE color cut, as applied in Zhou et al. 2021, can be very effective for selecting redshift ≳ 0.3 galaxies) in the sweep catalogs.

Name	Type	Description
`RELEASE`	int16	Integer denoting the camera and filter set used, which will be unique for a given processing run of the data (RELEASE is documented here)
`BRICKID`	int32	A unique Brick ID (in the range [1, 662174])
`OBJID`	int32	Catalog object number within this brick; a unique identifier hash is `RELEASE,BRICKID,OBJID`; `OBJID` spans [0,N-1] and is contiguously enumerated within each blob
`Z_SPEC`	float32	spectroscopic redshift, if available
`SURVEY`	char[12]	source of the spectroscopic redshift
`Z_PHOT_MEAN`	float32	photo-z derived from the mean of the photo-z PDF
`Z_PHOT_MEDIAN`	float32	photo-z derived from the median of the photo-z PDF
`Z_PHOT_STD`	float32	standard deviation of the photo-zs derived from the photo-z PDF
`Z_PHOT_L68`	float32	lower bound of the 68% confidence region, derived from the photo-z PDF
`Z_PHOT_U68`	float32	upper bound of the 68% confidence region, derived from the photo-z PDF
`Z_PHOT_L95`	float32	lower bound of the 95% confidence region, derived from the photo-z PDF
`Z_PHOT_U95`	float32	upper bound of the 68% confidence region, derived from the photo-z PDF
`TRAINING`	boolean	whether or not the spectroscopic redshift is used in photometric redshift training
`KFOLD`	int16	index of the subset in the 10-fold cross-validation
`Z_PHOT_MEAN_I`	float32	photo-z derived from the mean of the photo-z PDF (including \(i\)-band fluxes)
`Z_PHOT_MEDIAN_I`	float32	photo-z derived from the median of the photo-z PDF (including \(i\)-band fluxes)
`Z_PHOT_STD_I`	float32	standard deviation of the photo-zs derived from the photo-z PDF (including \(i\)-band fluxes)
`Z_PHOT_L68_I`	float32	lower bound of the 68% confidence region, derived from the photo-z PDF (including \(i\)-band fluxes)
`Z_PHOT_U68_I`	float32	upper bound of the 68% confidence region, derived from the photo-z PDF (including \(i\)-band fluxes)
`Z_PHOT_L95_I`	float32	lower bound of the 95% confidence region, derived from the photo-z PDF (including \(i\)-band fluxes)
`Z_PHOT_U95_I`	float32	upper bound of the 68% confidence region, derived from the photo-z PDF (including \(i\)-band fluxes)
`TRAINING_I`	boolean	whether or not the spectroscopic redshift is used in photometric redshift training (including \(i\)-band fluxes)
`KFOLD_I`	int16	index of the subset in the 10-fold cross-validation (including \(i\)-band fluxes)

Work which uses the photometric redshift sweeps should cite Zhou et al. (2023) and include the additional acknowledgment for photometric redshifts.

Foreground object masks (`masking/*`)

The foreground object masks were used to set the BRIGHT, MEDIUM, GALAXY and CLUSTER bits described on the DR10 bitmasks page. Files in the masking directory other than gaia-mask-dr10.fits.gz are generally described as part the overview of the external catalogs used for masking, and have data models that are detailed as part of the Siena Galaxy Atlas (SGA).

gaia-mask-dr10.fits.gz

A FITS binary table with a single HDU containing information about the Tycho-2 and Gaia EDR3 stars used to set the BRIGHT and MEDIUM bits described on the DR10 bitmasks page. See also the general overview of the external catalogs used for masking.

Name	Type	Units	Description
`ra`	float64	deg	Right ascension from the Gaia EDR3 or Tycho-2 catalog
`dec`	float64	deg	Declination from the Gaia EDR3 or Tycho-2 catalog
`ref_cat`	char[2]		Reference catalog source for this star: "T2" for Tycho-2, "GE" for Gaia EDR3
`ref_id`	int64		Reference catalog identifier for this star; Tyc11,000,000+Tyc210+Tyc3 for Tycho-2; "sourceid" for Gaia EDR3
`ref_epoch`	float32	yr	Reference catalog reference epoch (eg, 2016.0 for Gaia EDR3)
`mag`	float32	mag	Gaia G-band mag for Gaia EDR3; V_T for Tycho-2 when available, otherwise Hipparcos magnitude
`mask_mag`	float32	mag	Magnitude used for masking: the lesser of `mag` or (`zguess` + 1)
`radius`	float32	deg	Masking radius
`radius_pix`	int64	pix	Masking radius in 0.262 arcsec "brick" pixels
`pmra`	float32	mas/yr	Reference catalog proper motion in RA direction (\(\mu_\alpha^*\equiv\mu_\alpha\cos\delta\)) in the ICRS at `ref_epoch`
`pmdec`	float32	mas/yr	Reference catalog proper motion in Dec direction (\(\mu_\delta\)) in the ICRS at `ref_epoch`
`parallax`	float32	mas	Reference catalog parallax
`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
`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/mas²	Reference catalog inverse-variance on `parallax`
`in_desi`	boolean		In the DESI footprint?
`istycho`	boolean		From, or was matched to, the Tycho-2 catalog?
`isgaia`	boolean		From, or was matched to, the Gaia EDR3 catalog?
`isbright`	boolean		Is a `BRIGHT` star? `BRIGHT` stars are all Tycho-2 stars, plus Gaia EDR3 stars with `mask_mag` < 13 (see also the DR10 bitmasks page)
`ismedium`	boolean		Is a `MEDIUM` star? `MEDIUM` stars are Gaia EDR3 stars with `mask_mag` < 16 (see also the DR10 bitmasks page)
`pointsource`	boolean		Does the star pass the Legacy Surveys Gaia EDR3 point source cut?
`donotfit`	boolean		Does the object match an SGA galaxy? If `True` then the object will appear in the Tractor catalogs as a "DUP" source.
`decam_mag_g`	float32	mag	The estimated DECam \(g\) magnitude for Gaia EDR3 stars based on the \(G\) and \(Bp-Rp\) color
`decam_mag_r`	float32	mag	The estimated DECam \(r\) magnitude for Gaia EDR3 stars based on the \(G\) and \(Bp-Rp\) color
`decam_mag_i`	float32	mag	The estimated DECam \(i\) magnitude for Gaia EDR3 stars based on the \(G\) and \(Bp-Rp\) color
`decam_mag_z`	float32	mag	The estimated DECam \(z\) magnitude for Gaia EDR3 stars based on the \(G\) and \(Bp-Rp\) color
`zguess`	float32	mag	The estimated \(z\) magnitude for Tycho-2 stars from matching to 2MASS and estimating \(V\) to \(z\) transformations based on APASS.
`brickname`	char[8]		Name of brick, encoding the brick sky position, eg "1126p222" near RA=112.6, Dec=+22.2
`ibx`	int32		Integer brick pixel X coordinate (0-indexed) of this star
`iby`	int32		Integer brick pixel Y coordinate (0-indexed) of this star
`gaia_phot_g_mean_mag`	float32	mag	Gaia EDR3 G band magnitude
`gaia_phot_g_mean_flux_over_error`	float32		Gaia EDR3 G band signal-to-noise
`gaia_phot_g_n_obs`	int32		Gaia EDR3 G band number of observations
`gaia_phot_bp_mean_mag`	float32	mag	Gaia EDR3 BP magnitude
`gaia_phot_bp_mean_flux_over_error`	float32		Gaia EDR3 BP signal-to-noise
`gaia_phot_rp_mean_mag`	float32	mag	Gaia EDR3 RP magnitude
`gaia_phot_rp_mean_flux_over_error`	float32		Gaia EDR3 RP signal-to-noise
`gaia_astrometric_excess_noise`	float32		Gaia EDR3 astrometric excess noise
`gaia_astrometric_excess_noise_sig`	float32		Gaia EDR3 astrometric excess noise uncertainty
`gaia_duplicated_source`	boolean		Gaia EDR3 duplicated source flag
`gaia_phot_bp_rp_excess_factor`	float32		Gaia EDR3 BP/RP excess factor
`gaia_astrometric_sigma5d_max`	float32	mas	Gaia EDR3 longest semi-major axis of the 5-d error ellipsoid
`gaia_astrometric_params_solved`	uint8		Which astrometric parameters were estimated for a Gaia EDR3 source
`gaia_ipd_frac_multi_peak`	int8		Gaia EDR3 percent of successful windows from the Image Parameters Determination code with more than one peak
`gaia_ipd_gof_harmonic_amplitude`	float32		Gaia EDR3 amplitude of the Image Parameters Determination code goodness-of-fit versus the position angle of a scan
`gaia_ruwe`	float32		Gaia EDR3 renormalized unit weight error

Image Stacks (`south/coadd/*`)

Image stacks are on tangent-plane (WCS TAN) projections, 3600 × 3600 pixels, at 0.262 arcseconds per pixel.

<AAA>/<brick>/legacysurvey-<brick>-blobmodel-<filter>.fits.fz

The Tractor's model prediction of the images, similar to <AAA>/<brick>/legacysurvey-<brick>-model-<filter>.fits.fz, below, except that the models are clipped to the blobs within which they are measured. In other words, the models used to derive the maps in these files are not extrapolated beyond the pixels in the blobs that are used to fit the models.

<AAA>/<brick>/legacysurvey-<brick>-ccds.fits

FITS binary table with the list of CCD images that were used in this brick. Contains the same columns as survey-ccds-decam-dr10.fits.gz, and also contains the additional columns listed below.

Column	Type	Description
`ccd_x0`	int16	Minimum x image coordinate overlapping this brick
`ccd_y0`	int16	Minimum y image coordinate overlapping this brick
`ccd_x1`	int16	Maximum x image coordinate overlapping this brick
`ccd_y1`	int16	Maximum y image coordinate overlapping this brick
`brick_x0`	int16	Minimum x brick image coordinate overlapped by this image
`brick_x1`	int16	Maximum x brick image coordinate overlapped by this image
`brick_y0`	int16	Minimum y brick image coordinate overlapped by this image
`brick_y1`	int16	Maximum y brick image coordinate overlapped by this image
`psfnorm`	float32	Same as `psfnorm` in the ccds-annotated- file
`galnorm`	float32	Same as `galnorm` in the ccds-annotated- file
`skyver`	char[8]	Git version of the sky calibration code
`psfver`	char[21]	Git version of the PSF calibration code
`skyplver`	char[7]	Community Pipeline (CP) version of the input to sky calibration
`psfplver`	char[7]	CP version of the input to PSF calibration
`co_sky`	float32

<AAA>/<brick>/legacysurvey-<brick>-chi2-<filter>.fits.fz

Stacked χ² image, which is approximately the summed χ² values from the single-epoch images.
<AAA>/<brick>/legacysurvey-<brick>-depth-<filter>.fits.fz
Stacked depth map in units of the point-source flux inverse-variance at each pixel.
- The 5σ point-source depth can be computed as \(5 / \sqrt(\mathrm{depth\_ivar})\) .
<AAA>/<brick>/legacysurvey-<brick>-galdepth-<filter>.fits.fz
Stacked depth map in units of the canonical galaxy flux inverse-variance at each pixel. The canonical galaxy is an exponential profile with effective radius 0.45" and round shape.
- The 5σ galaxy depth can be computed as \(5 / \sqrt(\mathrm{galdepth\_ivar})\) .
<AAA>/<brick>/legacysurvey-<brick>-image-<filter>.fits.fz
Stacked image centered on a brick location covering 0.25° × 0.25°. The primary HDU contains the coadded image (inverse-variance weighted coadd), in units of nanomaggies per pixel.
- NOTE: These are not the images used by Tractor, which operates on the single-epoch images.
- NOTE: These images are resampled using Lanczos-3 resampling.
- NOTE: Images in WISE bands are on the Vega system, all other flux-related quantities in DR10 are reported on the AB system. The description page lists the Vega-to-AB conversions recommended by the WISE team.

<AAA>/<brick>/legacysurvey-<brick>-invvar-<filter>.fits.fz
Inverse variance image corresponding to the legacysurvey-<brick>-image-<filter>.fits.fz file based on the sum of the inverse-variances of the individual input images in units of 1/(nanomaggies)² per pixel.
- NOTE: These are not the inverse variance maps used by Tractor, which operates on the single-epoch images.
- NOTE: Images in WISE bands are on the Vega system, all other flux-related quantities in DR10 are reported on the AB system. The description page lists the Vega-to-AB conversions recommended by the WISE team.
<AAA>/<brick>/legacysurvey-<brick>-maskbits.fits.fz
Bitmask of possible problems with pixels in this brick.
- HDU1: The optical bitmasks, corresponding to MASKBITS on the DR10 bitmasks page.
- HDU2: The WISE W1 bitmasks, corresponding to WISEMASK_W1 on the DR10 bitmasks page.
- HDU3: The WISE W2 bitmasks, corresponding to WISEMASK_W2 on the DR10 bitmasks page.
<AAA>/<brick>/legacysurvey-<brick>-model-<filter>.fits.fz
Stacked model image centered on a brick location covering 0.25° × 0.25°.
- The Tractor's idea of what the coadded images should look like; the Tractor's model prediction.
- NOTE: Images in WISE bands are on the Vega system, all other flux-related quantities in DR10 are reported on the AB system. The description page lists the Vega-to-AB conversions recommended by the WISE team.
<AAA>/<brick>/legacysurvey-<brick>-nexp-<filter>.fits.fz

Number of good (unmasked) exposures contributing to each pixel of the stacked images.
<AAA>/<brick>/legacysurvey-<brick>-psfsize-<filter>.fits.fz

Weighted average PSF FWHM in arcsec at each pixel of the stacked images.
<AAA>/<brick>/legacysurvey-<brick>-blobmodel.jpg

JPEG image of the Tractor's model images, where the model fits have been clipped to the blobs within which the models are measured. Uses the \(g,r,i,z\) filters as the colors.
<AAA>/<brick>/legacysurvey-<brick>-image.jpg

JPEG image of the calibrated image using the \(g,r,i,z\) filters as the colors.
<AAA>/<brick>/legacysurvey-<brick>-model.jpg

JPEG image of the Tractor's model image using the \(g,r,i,z\) filters as the colors.
<AAA>/<brick>/legacysurvey-<brick>-resid.jpg

JPEG image of the residual image (data minus model) using the \(g,r,i,z\) filters as the colors.
<AAA>/<brick>/legacysurvey-<brick>-wise.jpg

JPEG image of the calibrated image using the WISE filters as the colors.
<AAA>/<brick>/legacysurvey-<brick>-wisemodel.jpg

JPEG image of the model image using the WISE filters as the colors.
<AAA>/<brick>/legacysurvey-<brick>-wiseresid.jpg

JPEG image of the residual image (data minus model) using the WISE filters as the colors.

Other Files

Much additional information is available as part of the DESI Legacy Imaging Surveys Data Releases, including, in separate directories, statistics of the Tractor fits (south/metrics), code outputs from the fitting processes (south/logs) and additional files detailing the calibrations (calib). We don't expect that most users will need a description of these files, but contact us if you require more information.

Raw Data

See the raw data page.

Footnotes