Description

The Dark Energy Survey (DES) is a 5000 square degree survey of the Southern sky in grizY aimed at understanding the accelerating expansion of the Universe and the nature of dark energy. DES uses four complementary measurements to probe the evolution of the Universe: weak gravitational lensing, galaxy cluster counts, the large-scale clustering of galaxies (including baryon acoustic oscillations), and the distances to type Ia supernovae. DES uses the Dark Energy Camera (DECam), a 570 Megapixel CCD imaging camera with a 3 square degree field of view installed at the prime focus of on the Blanco 4m telescope at the Cerro Tololo Interamerican Observatory in northern Chile. DES observed for a period of six years (2013-2019), and has collected information from roughly 550 million distant galaxies and 150 million Milky Way stars. DES has also performed a 27 square degree time domain survey aimed at discovering thousands of supernova and other transients. The DES webpage contains a full description of the survey.

The des_dr2.main table and des_dr1.main table have been crossmatched against our default reference datasets within a 1.5 arcsec radius, nearest neighbor only. These tables will appear with x1p5 in their name in our table browser. Example: des_dr2.x1p5__main__gaia_dr3__gaia_source.

DES survey footprint from DES Collaboration (2021).

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Goals

The primary goal of the Dark Energy Survey is to measure the cosmic acceleration of the Universe with high precision. It does this with four complementary cosmological probes:
  • Supernovae. DES observes a 27 square degree area, distributed over several fields, with a weekly cadence aimed at discovering thousands of supernovae for use for cosmology.
  • Weak gravitational lensing. DES measures the total matter content and structure of the Universe via the weak gravitational lensing of distant galaxies.
  • Galaxy clusters. DES detects tens of thousands of galaxy clusters, the most massive gravitationally bound systems in the Universe.
  • Galaxy clustering. DES measures the spatial distribuiton of galaxies which is a sensitive probe of large-scale structure and the primordial distribution of matter.
The DES data enable many other exciting scientific studies, which can be explored through the DES public data releases.

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Data Releases

DES DR2

Documentation for DES DR2 can be found in DES Collaboration (2021).

DES DR2 Summary
Area covered ~5000 deg2
Bands grizY
Median catalog depth for 1.95 arcsec diameter aperture at S/N~10 in grizY 24.7, 24.4, 23.8, 23.1, 21.7 mag
Median PSF FWHM in grizY 1.11, 0.95, 0.88, 0.83, 0.90 arcsec
Median astrometric internal precision ~27 mas
Number of co-added image tiles / exposures 10,169 / 96,263
Number of objects / galaxies / stellar sources 691,483,608 / 543 million / 145 million
DES DR2 Tables
Table Name Description
coverage Coverage table; fraction of the Healpix 4096 (Nest) pixel covered by a certain band (values between 0 and 1)
flux Object flux table
mag Object magnitude table
main Main photometry; summary table

DES DR1

Documentation on DES DR1 can be found in DES Collaboration (2018).

DES DR1 Summary
Area covered ~5000 deg2
Bands grizY
Median catalog depth for 1.95 arcsec diameter aperture at S/N~10 in grizY 24.45, 24.3, 23.5, 22.90, 21.70 mag
Median PSF FWHM in grizY 1.12, 0.96, 0.88, 0.84, 0.90 arcsec
Median astrometric internal precision ~30 mas
Number of co-added image tiles 10,338
Number of objects / galaxies / stellar sources 399,263,026 / 310 million / 80 million
DES DR1 Tables
Table Name Description
des_galex GALEX (AIS) 1-arcsec crossmatch v. DES DR1
des_hsc2 HSC2 1-arcsec crossmatch v. DES DR1
des_simbad SIMBAD 1-arcsec crossmatch v. DES DR1
flux Object flux table
galaxies Galaxies in DES DR1
img2coadd Images contributing to coadded tiles
mag Object magnitude table
main Main object summary table
tile_info Tile information table
DES DR1 Value-Added Catalogs
Table Name Description
baosample DES_Y1A1_LSSBAO_v1.1_CATALOG.fits. Main BAO sample catalog detailed in Crocce et al. (2018)
im3shape Galaxy shape catalogues using a maximum-likelihood bulge/disc model calibrated using simulations, applied to r-band data, yielding 21.9M objects
mock Galaxy mock catalogues of the Baryonic Acoustic Oscillation (BAO) angular distance using only photometry (for details, see https://ui.adsabs.harvard.edu/abs/2018MNRAS.479...94A/abstract)
mof Multi-Object Fitting (MOF) Catalogs (for details, see https://des.ncsa.illinois.edu/releases/y1a1/key-catalogs/key-mof)
morph Morphology Catalog (for details, see https://des.ncsa.illinois.edu/releases/y1a1/gold/morphology)
photo_z Photometric redshifts catalog (for details, see https://des.ncsa.illinois.edu/releases/y1a1/key-catalogs/key-photoz)
psf Point spread function catalog (for details, see https://des.ncsa.illinois.edu/releases/y1a1/key-catalogs/key-psf)
sgsep_cosmos_tests_v2 Star-galaxy separation catalog, covering DES observations from the Science Verification period and other DECam observations over the COSMOS field (for more details, see https://des.ncsa.illinois.edu/releases/y1a1/gold/classification)
sgsep_hsc_tests_v2 Star-galaxy separation catalog, covering DES observations from the Science Verification period over two specific fields with Hubble Space Telescope observations (downloaded from the https://archive.stsci.edu/hst/hsc/ site) with the ACS camera (other than COSMOS) appropriate for star-galaxy separation tests (for more details, see https://des.ncsa.illinois.edu/releases/y1a1/gold/classification)
sgsep_stripe82_tests_v2 Star-galaxy separation catalog, covering stripe 82 observations from SDSS with DES Y1 data (for more details, see https://des.ncsa.illinois.edu/releases/y1a1/gold/classification)
sgsep_validation_masked_v3 Star-galaxy separation catalog, covering This file covers observations in the main Y1 footprint with selected columns from Gold, MOF, photo-z and star-galaxy classifiers (for more details, see https://des.ncsa.illinois.edu/releases/y1a1/gold/classification)
sgsep_vvds_tests_v2 Star-galaxy separation catalog, voering VVDS observations with DES from the Science Verification period (for more details, see https://des.ncsa.illinois.edu/releases/y1a1/gold/classification)
shape_metacal_flux_griz Galaxy shape catalogues using a Gaussian model with an innovative internal calibration scheme, applied to riz-bands, yielding 34.8M objects
shape_metacal_riz_unblind Galaxy shape catalogues using a Gaussian model with an innovative internal calibration scheme, applied to riz-bands, yielding 34.8M objects
DES Y3 cosmology Value-Added Catalogs
Table Name Description
y3_gold Dark Energy Survey Year 3 - Cosmology Photometric Data Set
y3_gold_footprint Dark Energy Survey Year 3 - Cosmology Photometric Data Set, Foot Print
y3_gold_surveyconditions Dark Energy Survey Year 3 - Cosmology Photometric Data Set, Survey Conditions

DES SVA1

For a full description of DES SVA1, visit the DESDM page at NCSA (https://opensource.ncsa.illinois.edu/confluence/display/DESDM/DES+SVA1+Data+Products).

DES SVA1 Tables
Table Name Description
gold_annz2_pdf The PDFs have the following binning in redshift: z_min = 0.00, z_max = 1.8, nbins = 180
gold_annz2_point The structure of the point estimate files are identical. They each contain two columns: the SVA1 unique object identifier and the mean photo-z for that object.
gold_bpz_pdf The PDFs have the following binning in redshift: z_min = 0.005, z_max = 2.505 , nbins = 250
gold_bpz_point The structure of the point estimate files are identical. They each contain two columns: the SVA1 unique object identifier and the mean photo-z for that object.
gold_catalog The SVA1 GOLD catalog consists of basic astrometry, photometry, and object classification for 25,227,559 objects.
gold_im3shape This catalog includes the shear estimates made using the Im3Shape algorithm, described in Section 7.3 of Jarvis et al, 2015.
gold_ngmix This catalog includes the shear estimates made using the NGMix algorithm, described in Section 7.4 of Jarvis et al, 2015.
gold_skynet_pdf The PDFs have the following binning in redshift: z_min = 0.005, z_max = 1.8, nbins = 200
gold_skynet_point The structure of the point estimate files are identical. They each contain two columns: the SVA1 unique object identifier and the mean photo-z for that object.
gold_tpz_pdf The PDFs have the following binning in redshift: z_min = 0.0012625, z_max = 1.9962625, nbins = 200
gold_tpz_point The structure of the point estimate files are identical. They each contain two columns: the SVA1 unique object identifier and the mean photo-z for that object.
gold_wlinfo This catalog is merely for convenience, containing only information derived from other SVA1 catalogs.
redmagic_bright redMaGiC red galaxy catalog; bright redMaGiC samples. See Rozo et al. (2015), Table B2.
redmagic_faint redMaGiC red galaxy catalog; faint redMaGiC samples. See Rozo et al. (2015), Table B2.
redmapper_exp_area The RedMaPPer expanded catalog. Effective Area. See Rykoff et al. (2016), Table 12.
redmapper_exp_catalog The RedMaPPer expanded catalog. Cluster Catalog. See Rykoff et al. (2016), Table 8.
redmapper_exp_members The RedMaPPer expanded catalog. Member Catalog. See Rykoff et al. (2016), Table 9.
redmapper_exp_randoms The RedMaPPer expanded catalog. Random Point. See Rykoff et al. (2016), Table 11.
redmapper_exp_zmask The RedMaPPer expanded catalog. Zmask. See Rykoff et al. (2016), Table 10.
redmapper_pub_area The fiducial catalog with a more conservative footprint and star/galaxy separation. Effective Area. See Rykoff et al. (2016), Table 12.
redmapper_pub_catalog The fiducial catalog with a more conservative footprint and star/galaxy separation. Cluster Catalog. See Rykoff et al. (2016), Table 8.
redmapper_pub_members The fiducial catalog with a more conservative footprint and star/galaxy separation. Member Catalog. See Rykoff et al. (2016), Table 9.
redmapper_pub_randoms The fiducial catalog with a more conservative footprint and star/galaxy separation. Random Point. See Rykoff et al. (2016), Table 11.
redmapper_pub_zmask The fiducial catalog with a more conservative footprint and star/galaxy separation. Zmask. See Rykoff et al. (2016), Table 10.

To view the schema of any of these tables, use the Query Tool.


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Data Reduction

The DES data are processed through the DES Data Management (DESDM) pipeline, which includes image detrending and photometry (Morganson et al. 2018). The photometry is performed with modified versions of the Astromatic software suite, in particular the SExtractor and PSFEx packages. Users of these packages will find many of the column names in the DES tables to be familiar.

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