We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single-epoch images, co-added images, co-added source catalogs, and associated products and services assembled over the first 3 yr of DES science operations. DES DR1 is based on optical/near-infrared imaging from 345 distinct nights (2013 August to 2016 February) by the Dark Energy Camera mounted on the 4 m Blanco telescope at the Cerro Tololo Inter-American Observatory in Chile. We release data from the DES wide-area survey covering ∼5000 deg 2 of the southern Galactic cap in five broad photometric bands, grizY. DES DR1 has a median delivered point-spread function of = g 1.12, r=0.96, i=0.88, z=0.84, and Y=0 90 FWHM, a photometric precision of <1% in all bands, and an astrometric precision of 151 mas. The median co-added catalog depth for a 1 95 diameter aperture at signal-to-noise ratio (S/N)=10 is g=24.33, r=24.08, i=23.44, z=22.69, and Y=21.44 mag. DES DR1 includes nearly 400 million distinct astronomical objects detected in ∼10,000 co-add tiles of size 0.534 deg 2 produced from ∼39,000 individual exposures. Benchmark galaxy and stellar samples contain ∼310 million and ∼80 million objects, respectively, following a basic object quality selection. These data are accessible through a range of interfaces, including query web clients, image cutout servers, jupyter notebooks, and an interactive co-add image visualization tool. DES DR1 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

Abstract. GaussFit is a new computer program for solving least squares and robust estimation problems. It has a number of unique features, including a complete programming language designed especially to formulate estimation problems, a built-in compiler and interpreter to support the programming language, and a built-in algebraic manipulator for calculating the required partial derivatives analytically. These features make GaussFit very easy to use, so that even complex problems can be set up and solved with minimal effort. GaussFit can correctly handle many cases of practical interest: nonlinear models, exact constraints, correlated observations, and models where the equations of condition contain more than one observed quantity. An experimental robust estimation capability is built into GaussFit so that data sets contaminated by outliers can be handled simply and efficiently.

We present the second public data release of the Dark Energy Survey, DES DR2, based on optical/near-infrared imaging by the Dark Energy Camera mounted on the 4 m Blanco telescope at Cerro Tololo Inter-American Observatory in Chile. DES DR2 consists of reduced single-epoch and coadded images, a source catalog derived from coadded images, and associated data products assembled from 6 yr of DES science operations. This release includes data from the DES wide-area survey covering ∼5000 deg 2 of the southern Galactic cap in five broad photometric bands, grizY. DES DR2 has a median delivered point-spread function FWHM of g = 1.11″, r = 0.95″, i = 0.88″, z = 0.83″, and Y = 0 90, photometric uniformity with a standard deviation of < 3 mmag with respect to Gaia DR2 G band, a photometric accuracy of ∼11 mmag, and a median internal astrometric precision of ∼27 mas. The median coadded catalog depth for a 1 95 diameter aperture at signal-to-noise ratio = 10 is g = 24.7, r = 24.4, i = 23.8, z = 23.1, and Y = 21.7 mag. DES DR2 includes ∼691 million distinct astronomical objects detected in 10,169 coadded image tiles of size 0.534 deg 2 produced from 76,217 single-epoch images. After a basic quality selection, benchmark galaxy and stellar samples contain 543 million and 145 million objects, respectively. These data are accessible through several interfaces, including interactive image visualization tools, web-based query clients, image cutout servers, and Jupyter notebooks. DES DR2 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

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