# Legacy Survey Files

Top level directory for web access:

https://portal.nersc.gov/cfs/cosmo/data/legacysurvey/dr6/

Top level directory local to NERSC computers (for collaborators):

/global/cfs/cdirs/cosmo/data/legacysurvey/dr6/

## 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 DR6. 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.

### survey-bricks-dr6.fits.gz

A FITS binary table with information that summarizes the contents of each brick for DR6.

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 SIMP (there should be 0 such objects)

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 SFD 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 NOIRLab Community Pipeline as, e.g., cosmic rays or saturation, 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-*fits.gz

FITS binary table with almanac information about each individual CCD image in each band. There is one file for each of:

• 90prime-g: BASS $g$-band

• 90prime-r: BASS $r$-band

• mosaic-z: MzLS $z$-band

These files contain information regarding the photometric and astrometric zero points for each CCD of every image that is part of the DR6 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 $30 * 10^{((25.04 - 22.5) / 2.5)} = 311.3$ counts.

Column

Type

Description

image_filename

char[55]

Path to FITS image, eg "decam/CP20140810_g_v2/c4d_140815_235218_ooi_g_v2.fits.fz"

image_hdu

int16

FITS HDU number in the image_filename file where this image can be found

camera

char[7]

The camera that took this image

expnum

int32

Exposure number, eg 348224

ccdname

char[4]

CCD name (see Legacy Survey camera layout), eg "N10", "S7"

object

char[24]

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, 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

fwhm

float32

FWHM of observation

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

cd1_2

float32

cd2_1

float32

cd2_2

float32

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]

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)

ccd_cuts

int32

(ignore)

### survey-ccds-dr6plus.kd.fits

As for the survey-ccds-*.fits.gz files but limited by the depth of each observation. This file contains all of the CCDs actually used for the DR6 reductions. Columns are the same as for survey-ccds-*.fits.gz files.

### ccds-annotated-*.fits.gz

Versions of each of the survey-ccds-*.fits.gz file with additional information gathered during calibration pre-processing before running the Tractor reductions. One each for

• 90prime-g: BASS $g$-band

• 90prime-r: BASS $r$-band

• mosaic-z: MzLS $z$-band

Includes all of the columns in the survey-ccds-*.fits.gz file plus the following:

Column

Type

Description

annotated

boolean

(ignore)

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 SFD E(B-V) extinction in the tile, 0 for data from programs other than BASS, MzLS or DECaLS

plver

char[6]

Community Pipeline (CP) PLVER version string

ebv

float32

SFD 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

Note that two columns have different formats between the survey-ccds-*.fits.gz and ccds-annotated-*.fits.gz files. The camera column is char[6] and the object column is char[37].

### dr6-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_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)

### dr6-depth-summary.fits.gz

A summary of the depth histogram of the whole DR6 survey. 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 goes 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.

## External Files

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:

https://portal.nersc.gov/cfs/cosmo/data/legacysurvey/dr6/external/

Or on the NERSC computers (for collaborators) at:

/global/cfs/cdirs/cosmo/data/legacysurvey/dr6/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 1.0 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-dr6-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-dr6-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-dr6-dr14Q_v4_4.fits

HDU1 (the only HDU) contains Tractored survey photometry that is row-by-row-matched to the SDSS DR14 (partially) visually inspected quasar catalog (Paris et al. 2018) such that the photometric parameters in row "N" of survey-dr6-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-dr6-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-dr6-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-dr6-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-dr6-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-dr6-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-dr6-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

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).

### tractor/<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 Astro Data Lab [1] at datalab@noirlab.edu.

## Sweep Catalogs

### sweep/6.0/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. In addition to the columns listed below, the columns pertaining to optical data also have $U$, $I$ and $Y$-band entries (e.g. FLUX_U, FLUX_I, FLUX_Y), but, in DR6, these extra columns contain only zeros.

Name

Type

Units

Description

RELEASE

int32

Unique integer denoting the camera and filter set used (RELEASE is documented here)

BRICKID

int32

Brick ID [1,662174]

BRICKNAME

char[8]

Name of brick, encoding the brick sky position, eg "1126p222" near RA=112.6, Dec=+22.2

OBJID

int32

Catalog object number within this brick; a unique identifier hash is BRICKID,OBJID; OBJID spans [0,N-1] and is contiguously enumerated within each blob

TYPE

char[4]

Morphological model: "PSF"=stellar, "REX"="round exponential galaxy" = round EXP galaxy with a variable radius, "EXP"=exponential, "DEV"=deVauc, "COMP"=composite. 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 $W1$

FLUX_W2

float32

nanomaggies

WISE model flux in $W2$

FLUX_W3

float32

nanomaggies

WISE model flux in $W3$

FLUX_W4

float32

nanomaggies

WISE model flux in $W4$

FLUX_IVAR_G

float32

1/nanomaggies²

Inverse variance of FLUX_G

FLUX_IVAR_R

float32

1/nanomaggies²

Inverse variance of FLUX_R

FLUX_IVAR_Z

float32

1/nanomaggies²

Inverse variance of FLUX_Z

FLUX_IVAR_W1

float32

1/nanomaggies²

Inverse variance of FLUX_W1

FLUX_IVAR_W2

float32

1/nanomaggies²

Inverse variance of FLUX_W2

FLUX_IVAR_W3

float32

1/nanomaggies²

Inverse variance of FLUX_W3

FLUX_IVAR_W4

float32

1/nanomaggies²

Inverse variance of FLUX_W4

MW_TRANSMISSION_G

float32

Galactic transmission in $g$ filter in linear units [0,1]

MW_TRANSMISSION_R

float32

Galactic transmission in $r$ filter in linear units [0,1]

MW_TRANSMISSION_Z

float32

Galactic transmission in $z$ filter in linear units [0,1]

MW_TRANSMISSION_W1

float32

Galactic transmission in $W1$ filter in linear units [0,1]

MW_TRANSMISSION_W2

float32

Galactic transmission in $W2$ filter in linear units [0,1]

MW_TRANSMISSION_W3

float32

Galactic transmission in $W3$ filter in linear units [0,1]

MW_TRANSMISSION_W4

float32

Galactic transmission in $W4$ filter in linear units [0,1]

NOBS_G

int16

Number of images that contribute to the central pixel in $g$: filter for this object (not profile-weighted)

NOBS_R

int16

Number of images that contribute to the central pixel in $r$: filter for this object (not profile-weighted)

NOBS_Z

int16

Number of images that contribute to the central pixel in $z$: filter for this object (not profile-weighted)

NOBS_W1

int16

Number of images that contribute to the central pixel in $W1$: filter for this object (not profile-weighted)

NOBS_W2

int16

Number of images that contribute to the central pixel in $W2$: filter for this object (not profile-weighted)

NOBS_W3

int16

Number of images that contribute to the central pixel in $W3$: filter for this object (not profile-weighted)

NOBS_W4

int16

Number of images that contribute to the central pixel in $W4$: filter for this object (not profile-weighted)

RCHISQ_G

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $g$

RCHISQ_R

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $r$

RCHISQ_Z

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $z$

RCHISQ_W1

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $W1$

RCHISQ_W2

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $W2$

RCHISQ_W3

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $W3$

RCHISQ_W4

float32

Profile-weighted χ² of model fit normalized by the number of pixels in $W4$

FRACFLUX_G

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $g$ (typically [0,1])

FRACFLUX_R

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $r$ (typically [0,1])

FRACFLUX_Z

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $z$ (typically [0,1])

FRACFLUX_W1

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $W1$ (typically [0,1])

FRACFLUX_W2

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $W2$ (typically [0,1])

FRACFLUX_W3

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $W3$ (typically [0,1])

FRACFLUX_W4

float32

Profile-weighted fraction of the flux from other sources divided by the total flux in $W4$ (typically [0,1])

FRACMASKED_G

float32

Profile-weighted fraction of pixels masked from all observations of this object in $g$, strictly between [0,1]

FRACMASKED_R

float32

Profile-weighted fraction of pixels masked from all observations of this object in $r$, strictly between [0,1]

FRACMASKED_Z

float32

Profile-weighted fraction of pixels masked from all observations of this object in $z$, strictly between [0,1]

FRACIN_G

float32

Fraction of a source's flux within the blob in $g$, near unity for real sources

FRACIN_R

float32

Fraction of a source's flux within the blob in $r$, near unity for real sources

FRACIN_Z

float32

Fraction of a source's flux within the blob in $z$, near unity for real sources

ANYMASK_G

int16

Bitwise mask set if the central pixel from any image satisfies each condition in $g$

ANYMASK_R

int16

Bitwise mask set if the central pixel from any image satisfies each condition in $r$

ANYMASK_Z

int16

Bitwise mask set if the central pixel from any image satisfies each condition in $z$

ALLMASK_G

int16

Bitwise mask set if the central pixel from all images satisfy each condition in $g$

ALLMASK_R

int16

Bitwise mask set if the central pixel from all images satisfy each condition in $r$

ALLMASK_Z

int16

Bitwise mask set if the central pixel from all images satisfy each condition in $z$

WISEMASK_W1

uint8

W1 bright star bitmask, $2^0$ $(2^1)$ for southward (northward) scans

WISEMASK_W2

uint8

W2 bright star bitmask, $2^0$ $(2^1)$ for southward (northward) scans

PSFSIZE_G

float32

arcsec

Weighted average PSF FWHM in the $g$ band

PSFSIZE_R

float32

arcsec

Weighted average PSF FWHM in the $r$ band

PSFSIZE_Z

float32

arcsec

Weighted average PSF FWHM in the $z$ band

PSFDEPTH_G

float32

1/nanomaggies²

For a $5\sigma$ point source detection limit in $g$, $5/\sqrt(\mathrm{PSFDEPTH\_G})$ gives flux in nanomaggies and $-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_G})) - 9]$ gives corresponding magnitude

PSFDEPTH_R

float32

1/nanomaggies²

For a $5\sigma$ point source detection limit in $g$, $5/\sqrt(\mathrm{PSFDEPTH\_R})$ gives flux in nanomaggies and $-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_R})) - 9]$ gives corresponding magnitude

PSFDEPTH_Z

float32

1/nanomaggies²

For a $5\sigma$ point source detection limit in $g$, $5/\sqrt(\mathrm{PSFDEPTH\_Z})$ gives flux in nanomaggies and $-2.5[\log_{10}(5 / \sqrt(\mathrm{PSFDEPTH\_Z})) - 9]$ gives corresponding magnitude

GALDEPTH_G

float32

1/nanomaggies²

As for PSFDEPTH_G but for a galaxy (0.45" exp, round) detection sensitivity

GALDEPTH_R

float32

1/nanomaggies²

As for PSFDEPTH_R but for a galaxy (0.45" exp, round) detection sensitivity

GALDEPTH_Z

float32

1/nanomaggies²

As for PSFDEPTH_Z but for a galaxy (0.45" exp, round) detection sensitivity

WISE_COADD_ID

char[8]

unWISE coadd file name for the center of each object

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

## Image Stacks

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

FITS binary table with the list of CCD images that were used in this brick. Contains the same columns as survey-ccds-dr6plus.kd.fits, and also contains the additional columns:

Column

Type

Description

ccd_cuts

int32

(ignore)

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

plver

char[4]

Community Pipeline (CP) version

skyver

char[19]

Git version of the sky calibration code

wcsver

char[1]

Git version of the WCS calibration code

psfver

char[12]

Git version of the PSF calibration code

skyplver

char[4]

CP version of the input to sky calibration

wcsplver

char[4]

CP version of the input to WCS calibration

psfplver

char[4]

CP version of the input to PSF calibration

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: that these images are resampled using Lanczos-3 resampling.

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.

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.

Stacked χ² image, which is approximately the summed χ² values from the single-epoch images.

Stacked depth map in units of the point-source flux inverse-variance at each pixel.

• The 5σ point-source depth can be computed as $5 / \sqrt(\mathrm{depth\_ivar})$ .

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 $5 / \sqrt(\mathrm{galdepth\_ivar})$ .

Number of exposures contributing to each pixel of the stacked images.

JPEG image of calibrated image using the $g,r,z$ filters as the colors.

JPEG image of the Tractor's model image using the $g,r,z$ filters as the colors.
JPEG image of the residual image (data minus model) using the $g,r,z$ filters as the colors.