# Legacy Survey Files

Throughout this page <region> denotes either north for BASS/MzLS or south for DECaLS.

## Directory Structures

### At NERSC (for collaborators)

Top level directory:
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/
Top level directory for DECaLS data:
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/south/
Top level directory for MzLS/BASS data:
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/north/
Top level directories for sweeps catalogs:
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/south/sweep/
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/north/sweep/

## Summary Files

### survey-bricks.fits.gz

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 DR8. 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.

### <region>/survey-bricks-dr8-<region>.fits.gz

A FITS binary table with information that summarizes the contents of each brick for a region of DR8.

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_z int16 Median number of exposures in the unique area of the brick in z-band
nexphist_g int32[6] Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, or > 5 exposures in g
nexphist_r int32[6] Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, or > 5 exposures in r
nexphist_z int32[6] Histogram of number of pixels in the unique brick area with 0, 1, 2, 3, 4, or > 5 exposures in z
nobjs int16 Total number of BRICK_PRIMARY objects in this brick, of all types
npsf int16 Total number of BRICK_PRIMARY objects in this brick, of type PSF
nsimp int16 Total number of BRICK_PRIMARY objects in this brick, of type REX
nrex int16 Total number of BRICK_PRIMARY objects in this brick, of type REX
nexp int16 Total number of BRICK_PRIMARY objects in this brick, of type EXP
ndev int16 Total number of BRICK_PRIMARY objects in this brick, of type DEV
ncomp int16 Total number of BRICK_PRIMARY objects in this brick, of type COMP
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_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_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_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 $g$-band, based on ebv. See also MW_TRANSMISSION_R
trans_z float32 Median Milky Way dust transparency in $z$-band, based on ebv. See also MW_TRANSMISSION_Z
ext_g float32 Extinction in $g$-band
ext_r float32 Extinction in $r$-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

Note that, for the nexphist rows, pixels that are masked by the NOAO Community Pipeline as, e.g., cosmic rays or saturation (see, e.g. the ALLMASK/ANYMASK information on the DR8 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-<camera>-dr8.fits.gz

A FITS binary table with almanac information about each individual CCD image for each camera (where <camera> is one of 90prime for BASS, decam for DECaLS or mosaic for MzLS).

This file contains information regarding the photometric and astrometric zero points for each CCD of every image that is part of the DR8 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[120] Path to FITS image, e.g. "north/DECam_CP/CP20170729/c4d_170730_045351_ooi_g_v1.fits.fz"
image_hdu int16 FITS HDU number in the image_filename file where this image can be found
camera char[9] The camera that took this image e.g. "90prime"
expnum int64 Exposure number, eg 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[5] CCD name, e.g. "N10", "S7" for DECam
object char[35] Name listed in the object tag from the CCD header
propid char[10] NOAO Proposal ID that took this image, eg "2014B-0404"
filter char[1] Filter used for observation, eg "$g$", "$r$", "$z$"
exptime float32 Exposure time in seconds, eg 30
mjd_obs float64 Date of observation in MJD (in UTC system), eg 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, eg 2046
height int16 Height in pixels of this image, eg 4096
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)
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), eg 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 count level per pixel in the CP-processed frames measured (with iterative rejection) for each CCD in the image section [500:1500,1500:2500]
ccdskysb float32 Sky surface brightness (in AB mag/arcsec2)
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)
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 int32 (ignore)

### survey-ccds-<camera>-dr8.kd.fits

As for the survey-ccds-<camera>-dr8.fits.gz files but limited by the depth of each observation. These files contain the CCDs actually used for the DR8 reductions. Columns are the same as for the survey-ccds-<camera>-dr8.fits.gz files.

### ccds-annotated-<camera>-dr8.fits.gz

Versions of the survey-ccds-<camera>-dr8.fits.gz files with additional information gathered during calibration pre-processing before running the Tractor reductions.

Includes all of the columns in the survey-ccds-<camera>-dr8.fits.gz files plus the columns listed below. Note that string columns can have different lengths in the survey-ccds-<camera>-dr8.fits.gz and ccds-annotated-<camera>-dr8.fits.gz files. For example the camera column can change from char[9] to char[7] (see, e.g. legacypipe issue #379).

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 pipeline (not the CP) estimate of the sky level, average over the image, in ADU.
stdsky float32 Standard deviation of our sky level
maxsky float32 Max of our sky level
minsky float32 Min of our sky level
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_i^2)) 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 (pixels^2)
psf_my2 float32 PSF model second moment in y (pixels^2)
psf_mxy float32 PSF model second moment in x-y (pixels^2)
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 (deg 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

### <region>/dr8-<region>-depth.fits.gz

A concatenation of the depth histograms for each brick, for each region, 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_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)

### <region>/dr8-<region>-depth-summary.fits.gz

A summary of the depth histogram for a region of DR8. 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_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-inside-dr8-0.31.0-*.fits

Ten files of random points sampled across the CCDs that comprise the geometry of DR8. Random locations were generated across the footprint at a density of 5,000 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). Contains the following columns:

Column Type Description
RA float64 Right ascension at equinox J2000
DEC float64 Declination at equinox J2000
BRICKNAME char[8] Name of the brick
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_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 $g$, $5/\sqrt(\mathrm{PSFDEPTH\_R})$ gives flux in nanomaggies and $-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_R})) - 9]$ gives corresponding magnitude
PSFDEPTH_Z float32 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 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_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_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_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_Z float32 Inverse variance of APFLUX_Z
EBV float32 Galactic extinction E(B-V) reddening from SFD98
PHOTSYS char[1] 'N' for an MzLS/BASS location, 'S' for a DECaLS location
HPXPIXEL int64 HEALPixel containing this location at NSIDE=64 in the NESTED scheme

The 0.31.0 in the file names refers to the version of the desitarget code used to generate the random catalogs. The code is available on GitHub (see also here). The northern and southern imaging footprints overlap, so, randoms are resolved at a Declination of 32.375° and by the Galactic plane, such that locations at Dec > 32.375° that are north of the Galactic Plane have PHOTSYS set to "N".

### randoms/randoms-outside-dr8-0.31.0-*.fits

Ten files of random points in bricks that do not contain an observation in DR8 (that are "outside" of the DR8 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 5,000 per square degree and the order of the points within the file is also randomized. Contains the following columns:

Column Type Description
RA float64 Right ascension at equinox J2000
DEC float64 Declination at equinox J2000
BRICKNAME char[8] Name of the brick
NOBS_G int16 Always zero in this file.
NOBS_R 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/randoms-allsky-dr8-0.31.0.fits

The (randomly shuffled) combination of each of the randoms-inside-dr8-0.31.0-X.fits and randoms-outside-dr8-0.31.0-X.fits files (where X = 1, 2, 3 etc.). This creates ten "all-sky" random catalogs (at a density of 5,000 locations per square degree) where each brick is either populated with observations from the Legacy Surveys, or zeros. Contains the same columns as the randoms-inside-dr8-0.31.0-\*.fits files.

### randoms/survey-bricks-dr8-randoms-0.31.0.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 in the north, south, or outside of the footprint, respectively.
AREA_PER_BRICK float64 The area of the brick in square degrees.

## External Files (<region>/external/*)

The Legacy Survey photometric catalogs have been matched to the following external spectroscopic files from the SDSS, which can be accessed through the web at:
Or on the NERSC computers (for collaborators) at:
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/north/external/
/global/project/projectdirs/cosmo/data/legacysurvey/dr8/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.

### survey-dr8-<region>-specObj-dr14.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR14 spectrosopic pipeline file such that the photometric parameters in row "N" of survey-dr8-specObj-dr14.fits matches the spectroscopic parameters in row "N" of specObj-dr14.fits. The spectroscopic file is documented in the SDSS DR14 data model for specObj-dr14.fits.

### survey-dr8-<region>-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-dr8-dr12Q.fits matches the spectroscopic parameters in row "N" of DR12Q.fits. The spectroscopic file is documented in the SDSS DR12 data model for DR12Q.fits.

### survey-dr8-<region>-dr14Q_v4_4.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR14 visually inspected quasar catalog (Paris et al. 2018) such that the photometric parameters in row "N" of survey-dr8-dr14Q_v4_4.fits matches the spectroscopic parameters in row "N" of DR14Q_v4_4.fits. The spectroscopic file is documented in the SDSS DR14 data model for DR14Q_v4_4.fits.

### survey-dr8-<region>-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-dr8-Superset_dr12Q.fits matches 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-dr8-<region>-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-dr8-dr7Q.fits matches the spectroscopic parameters in row "N" of DR7qso.fit. The spectroscopic file is documented on the DR7 quasar catalog description page.

## Tractor Catalogs (<region>/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 region 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 $g$, $r$ 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 contact the NOAO Data Lab at datalab@noao.edu.

## Sweep Catalogs (<region>/sweep/*)

### 8.0/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   Unique integer denoting the camera and filter set used (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[4]   Morphological model: "PSF"=stellar, "REX"="round exponential galaxy" = round EXP galaxy with a variable radius, "EXP"=exponential, "DEV"=deVauc, "COMP"=composite, "DUP"==Gaia source fit by different model. Note that in some FITS readers, a trailing space may be appended for "PSF ", "EXP " and "DEV " since the column data type is a 4-character string
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, COMP. 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 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 $W1$ (AB system)
FLUX_W2 float32 nanomaggies WISE model flux in $W2$ (AB)
FLUX_W3 float32 nanomaggies WISE model flux in $W3$ (AB)
FLUX_W4 float32 nanomaggies WISE model flux in $W4$ (AB)
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 (AB system)
FLUX_IVAR_W2 float32 1/nanomaggies² Inverse variance of FLUX_W2 (AB)
FLUX_IVAR_W3 float32 1/nanomaggies² Inverse variance of FLUX_W3 (AB)
FLUX_IVAR_W4 float32 1/nanomaggies² 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_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 $g$ (see the DR8 bitmasks page)
ANYMASK_R int16   Bitwise mask set if the central pixel from any image satisfies each condition in $r$ (see the DR8 bitmasks page)
ANYMASK_Z int16   Bitwise mask set if the central pixel from any image satisfies each condition in $z$ (see the DR8 bitmasks page)
ALLMASK_G int16   Bitwise mask set if the central pixel from all images satisfy each condition in $g$ (see the DR8 bitmasks page)
ALLMASK_R int16   Bitwise mask set if the central pixel from all images satisfy each condition in $r$ (see the DR8 bitmasks page)
ALLMASK_Z int16   Bitwise mask set if the central pixel from all images satisfy each condition in $z$ (see the DR8 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_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
PSFDEPTH_W1 float32 1/nanomaggies² As for PSFDEPTH_G (and also on the AB system) but for WISE W1
PSFDEPTH_W2 float32 1/nanomaggies² 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
FRACDEV float32   Fraction of model in deVauc [0,1]
FRACDEV_IVAR float32   Inverse variance of FRACDEV
SHAPEDEV_R float32 arcsec Half-light radius of deVaucouleurs model (>0)
SHAPEDEV_R_IVAR float32 1/arcsec Inverse variance of SHAPEDEV_R
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
SHAPEEXP_R float32 arcsec Half-light radius of exponential model (>0)
SHAPEEXP_R_IVAR float32 1/arcsec2 Inverse variance of SHAPEEXP_R
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
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
REF_CAT char[2]   Reference catalog source for this star: "T2" for Tycho-2, "G2" for Gaia DR2, "L2" for the LSLGA, empty otherwise
REF_ID int64   Reference catalog identifier for this star; Tyc1*1,000,000+Tyc2*10+Tyc3 for Tycho2; "sourceid" for Gaia-DR2 and LSLGA
REF_EPOCH float32 yr Reference catalog reference epoch (eg, 2015.5 for Gaia DR2)
GAIA_PHOT_G_MEAN_MAG float32 mag Gaia G band magnitude
GAIA_PHOT_G_MEAN_FLUX_OVER_ERROR float32   Gaia G band signal-to-noise
GAIA_PHOT_BP_MEAN_MAG float32 mag Gaia BP magnitude
GAIA_PHOT_BP_MEAN_FLUX_OVER_ERROR float32   Gaia BP signal-to-noise
GAIA_PHOT_RP_MEAN_MAG float32 mag Gaia RP magnitude
GAIA_PHOT_RP_MEAN_FLUX_OVER_ERROR float32   Gaia RP signal-to-noise
GAIA_ASTROMETRIC_EXCESS_NOISE float32   Gaia astrometric excess noise
GAIA_DUPLICATED_SOURCE boolean   Gaia duplicated source flag (1/0 for True/False)
GAIA_PHOT_BP_RP_EXCESS_FACTOR float32   Gaia BP/RP excess factor
GAIA_ASTROMETRIC_SIGMA5D_MAX float32 mas Gaia longest semi-major axis of the 5-d error ellipsoid
GAIA_ASTROMETRIC_PARAMS_SOLVED uint8   Which astrometric parameters were estimated for a Gaia source
PARALLAX float32 mas Reference catalog parallax
PMRA float32 mas/yr Reference catalog proper motion in the RA direction
PMDEC float32 mas/yr Reference catalog proper motion in the Dec direction

### Photometric Redshift files (8.0-photo-z/sweep-<brickmin>-<brickmax>-pz.fits)

The Photometric Redshifts for the Legacy Surveys (PRLS, Zhou et al. (2020)) catalog is line-matched to the DR8 sweep catalogs as described above.

The photometric redshifts are computed using the random forest algorithm. Details of the photo-z training and performance can be found in Zhou et al. (2020). For computing the photo-z's, we require at least one exposure in $g$, $r$ 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-z's for all objects that meet the NOBS cut, only relatively bright objects have reliable photo-z's. As a rule of thumb, objects brighter than $z$-band magnitude of 21 are mostly reliable, whereas fainter objects are increasingly unreliable with large systematic offsets.

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

Name Type Description
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-z's 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
z_spec float32 spectroscopic redshift, if available
survey char[10] source of the spectroscopic redshift
training boolean whether or not the spectroscopic redshift is used in photometric redshift training

Work which uses this photometric redshift catalog should cite Zhou et al. (2020) and include the following acknowledgment: "The Photometric Redshifts for the Legacy Surveys (PRLS) catalog used in this paper was produced thanks to funding from the U.S. Department of Energy Office of Science, Office of High Energy Physics via grant DE-SC0007914."

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

• <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-<camera>-dr8.fits.gz, and also contains the additional columns listed below. Note that string columns can have different lengths in the survey-ccds-<camera>-dr8.fits.gz and legacysurvey-<brick>-ccds.fits files and can differ for <region> equal to <north> and <south>. For example the camera column can change from char[9] to char[7] (see, e.g. legacypipe issue #379).

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
wcsver char[1] Git version of the WCS calibration code
psfver char[7] Git version of the PSF calibration code
skyplver char[8] Community Pipeline (CP) version of the input to sky calibration
wcsplver char[5] CP version of the input to WCS calibration
psfplver char[8] CP version of the input to PSF calibration
• <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 DR8 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
Corresponding stacked inverse variance image 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 DR8 are reported on the AB system. The description page lists the Vega-to-AB conversions recommended by the WISE team.
Bitmask of possible problems with pixels in this brick.
• <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 DR8 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 exposures contributing to each pixel of the stacked images.
• <AAA>/<brick>/legacysurvey-<brick>-psfsize-<filter>.fits.fz
Number of exposures contributing to each pixel of the stacked images.
• <AAA>/<brick>/legacysurvey-<brick>-image.jpg
JPEG image of the calibrated image using the $g,r,z$ filters as the colors.
• <AAA>/<brick>/legacysurvey-<brick>-model.jpg
JPEG image of the Tractor's model image using the $g,r,z$ filters as the colors.
• <AAA>/<brick>/legacysurvey-<brick>-resid.jpg
JPEG image of the residual image (data minus model) using the $g,r,z$ 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.

## Forced Photometry Files (forced/<camera>/<EXPOS>/forced-<camera>-<EXPOSURE>.fits)

These files contain forced photometry results, for all CCDs that were included in the DR8 processing.

That is, after we produce the catalogs based on fitting to all images simultaneously, we go back to the individual CCDs, select the catalog objects that overlap, and ask what fluxes those objects should have to best match what is observed in the CCD. When selecting objects from the catalog, we resolve the north and south components using the same cut as in the sweep files and randoms.

We perform two fits. The first is regular forced photometry, where the position and profile of the sources are fixed, and all we are fitting is the flux. In the second fit, we compute the source-centered spatial derivatives and fit the amplitudes of those derivatives as well. For sources moving less than a pixel or two, this produces an approximate estimate of the motion of the source. Note that for Gaia sources, this is relative to the Gaia measured proper motion!

• forced/<camera>/<EXPOS>/forced-<camera>-<EXPOSURE>.fits

Where <camera> is one of 90prime for BASS, decam for DECaLS or mosaic for MzLS, <EXPOSURE> is the exposure number (not as an 8-character string, unlike some other data products), and <EXPOS> is the first 5 characters of the exposure number printed as an 8-character string.

This file contains a single FITS binary table for all the CCDs in this exposure, contatenated into one long table.

For the columns pertaining to the catalog objects, see the catalog description page.

Column Type Description
release int16 Unique integer denoting the camera and filter set used (RELEASE is documented here) for the catalog object
brickid int32 Unique Brick ID (in the range [1, 662174]) that the catalog object came from
brickname char[8] Name of brick, encoding the brick sky position, eg "1126p222" near RA=112.6, Dec=+22.2, of the catalog object
objid int32 Catalog object number within this brick; a unique identifier hash is release,brickid,objid
camera char[7] The camera for the CCD being measured, eg "decam"
expnum int64 The exposure number of the CCD being mesaured, eg 574299
ccdname char[4] The name of the CCD being measured, eg "N10" or "CCD4"
filter char[1] The filter of the CCD being measured ("g", "r" or "z")
mjd float64 The Modified Julian Date when the exposure was taken, in UTC, eg 57644.31537588
exptime float32 The exposure time in seconds, eg 90.0
psfsize float32 PSF FWHM in this exposure, in arcsec
ccd_cuts int64 Bit mask describing CCD image quality
airmass float32 Airmass of this observation
sky float32 Sky background surface brightness, in nanomaggies/arcsec²
psfdepth float32 Inverse-variance for the flux measured from a point source; for a $5\sigma$ point source detection limit use $5/\sqrt(\mathrm{psfdepth})$ for the flux in nanomaggies and $-2.5[\log_{10}(5 / \sqrt(\mathrm{psfdepth})) - 9]$ for the corresponding AB magnitude
galdepth float32 Inverse-variance for the flux measured from a nominal galaxy source (0.45" round exponential galaxy)
ra float64 Right Ascension in degrees
dec float64 Declination in degrees
flux float32 Measured flux for this catalog object in this CCD, in nanomaggies
flux_ivar float32 Inverse-variance of the flux measurement, in 1/nanomaggies²
fracflux float32 Profile-weighted fraction of the flux from other sources over total flux
rchisq float32 Profile-weighted χ² residual chi-squared per pixel
apflux float32[8] Aperture fluxes in this CCD, in nanomaggies, for aperture radii [0.5, 0.75, 1.0, 1.5, 2.0, 3.5, 5.0, 7.0] arcsec
apflux_ivar float32[8] Inverse-variance on apflux, in 1/nanomaggies²
x float32 Horizontal pixel position of the catalog source in this CCD, in zero-indexed pixels
y float32 Vertical pixel position of the catalog source in this CCD, in zero-indexed pixels
dra float32 When fitting for spatial derivatives, the motion of the source in the RA direction, in arcsec
ddec float32 Motion of the source in the Dec direction, in arcsec
dra_ivar float32 Inverse-variance on dra, in 1/arcsec|sup2|
ddec_ivar float32 Inverse-variance on ddec, in 1/arcsec|sup2|

## Splinesky Files (calib/<camera>/splinesky-*)

• splinesky-merged/<EXPOS>/<camera>-<EXPOSURE>.fits

Where <camera> is one of 90prime, decam or mosaic, <EXPOSURE> is the exposure number as an 8-character string and <EXPOS> is the first 5 characters of <EXPOSURE>.

This file contains all of the sky models for a given exposure number, as a single FITS binary table with 60 rows, one per CCD. Each row in this table contains the sky model for a single CCD. The splinesky files describe a smooth 2-dimensional function, implemented using the scipy RectBivariateSpline function. This is defined by a number of grid cell locations and function values at those locations, interpolated with a cubic spline. The spline grid cells for DR8 are ~256 pixels in size, and extend from edge to edge, so, for example DECam images (~2048 x 4096 pixels) have 9 x 17 cells.

For MzLS (mosaic) files, some early exposures lack an EXPNUM in the headers; these have a fake exposure number like 160125082555 corresponding to the date and time the image was taken (2016-01-25T08:25:55). For BASS (90prime) files, the exposure number comes from the DTACQNAM header card; for example, 20160710/d7580.0144.fits becomes exposure number 75800144.

Column Type Description
gridw int64 The number of grid cells in the horizontal direction
gridh int64 The number of grid cells in the vertical direction
gridvals float32 The spline values (an array of size gridh $\times$ gridw)
xgrid int32 The horizontal locations of the grid cells (an array of length gridw)
ygrid int32 The vertical locations of the grid cells (an array of length gridh)
order uint8 The order of the spline (i.e. 3 = cubic)
x0 int32 Pixel offset of the model in the x direction (always 0 for these files)
y0 int32 Pixel offset of the model in the y direction (always 0 for these files)
skyclass char[27] Always set to tractor.splinesky.SplineSky (the name of a Python class that is used to read the model)
legpipev char[19] Version of legacypipe used for this reduction
plver char[4] Community Pipeline (CP) version number
plprocid char[7] Unique, time-based, CP processing hash - see the plprocid page for how to convert this to a date
imgdsum int64 The DATASUM value from the image header (a checksum)
procdate char[19] CP processing date
sig1 float32 Estimated per-pixel noise in CP image units, from $1/\sqrt(\mathrm{median}(wt[good]))$ where $wt$ is the weight map and $good$ are un-masked pixels
sky_mode float32 Scalar mode of the image, estimated by fitting a quadratic to the histogram of unmasked pixels
sky_med float32 Scalar median of the image, based on unmasked pixels
sky_cmed float32 Median of the $2\sigma$-clipped image pixel values, based on unmasked pixels
sky_john float32 Starting from a 5-pixel boxcar average over the sky_cmed-subtracted pixels, find and mask $3\sigma$ sources (dilated by 3 pixels), then take the median of $2\sigma$-clipped pixels
sky_fine float32 RMS difference between a splinesky model at normal and at twice the resolution, to characterize the splinesky model had it more freedom
sky_p0 float32 Identical to sky_fine
sky_p10 float32 0th percentile of unmasked image pixels minus the splinesky model
sky_p20 float32 10th percentile of unmasked image pixels minus the splinesky model
sky_p30 float32 20th percentile of unmasked image pixels minus the splinesky model
sky_p40 float32 30th percentile of unmasked image pixels minus the splinesky model
sky_p50 float32 40th percentile of unmasked image pixels minus the splinesky model
sky_p60 float32 50th percentile of unmasked image pixels minus the splinesky model
sky_p70 float32 60th percentile of unmasked image pixels minus the splinesky model
sky_p80 float32 70th percentile of unmasked image pixels minus the splinesky model
sky_p90 float32 80th percentile of unmasked image pixels minus the splinesky model
sky_p100 float32 90th percentile of unmasked image pixels minus the splinesky model
expnum int64 Exposure number, eg 348224
ccdname char[4] CCD name, e.g. "N10", "S7" for DECam

## 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 (<region>/metrics), code outputs from the fitting processes (<region>/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

NOAO access to raw and calibrated images will be available a few weeks after the DR8 release date.

Raw and Calibrated Legacy Survey images are available from the NOAO Science Archive through the web portal (http://archive.noao.edu/search/query) and an ftp server. The input data used to create the stacked images, Tractor catalogs, etc. comprise images taken by the dedicated DESI Legacy Imaging Surveys project, as well as other images from NOAO telescopes.

### (i) Web interface

1. Query the NOAO Science Archive.
2. From the menu of "Available Collections" on the left, select the desired data release (e.g. LS-DR8).
3. Under "Data products - Raw data" check "Object".
4. Optionally, you may select data from specific filters, or restrict the search by other parameters such as sky coordinates, observing date, or exposure time.
5. Click "Search".
6. The Results page offers several different ways to download the data. See the Tutorials page for details.

### (ii) ftp sites

Following the organization of the Stacked images, Raw and Calibrated images are organized by survey brick, which are defined in the file survey-bricks-dr8.fits.gz for DR8. Both the main Tractor catalogs and Sweep catalogs include the BRICKNAME keyword (corresponding to <brick> with format <AAAa>c<BBB>).

For the calibrated images, filenames can be retrieved from the IMAGE_FILENAME keyword in each brick from legacysurvey-<brick>-ccds.fits. Additionally, each calibrated/<AAA>/<brick> contains an ASCII file with a list of EXPID and IMAGE_FILENAME (legacysurvey-<brick>-image_filename.txt). EXPID contains the exposure number and the CCD name with the format EXPNUM-ccd. There is one entry per CCD. Often, multiple CCDs from a given file are used so there are fewer unique filenames than the number of CCDs. Each legacysurvey-<brick>-image_filename.txt file contains the number of unique images in the last row (File Count).