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We present a study of quasar selection using the supernova fields of the Dark Energy Survey (DES). We used a quasar catalog from an overlapping portion of the SDSS Stripe 82 region to quantify the completeness and efficiency of selection methods involving color, probabilistic modeling, variability, and combinations of color/ probabilistic modeling with variability. In all cases, we considered only objects that appear as point sources in the DES images. We examine color selection methods based on the Wide-field Infrared Survey Explorer (WISE) mid- IR W1 - W2 color, a mixture of WISE and DES colors (g − i and i - W1), and a mixture of Vista Hemisphere Survey and DES colors (g − i and i − K ). For probabilistic quasar selection, we used XDQSO, an algorithm that employs an empirical multi-wavelength flux model of quasars to assign quasar probabilities. Our variability selection uses the multi-band χ2-probability that sources are constant in the DES Year 1 griz-band light curves. The completeness and efficiency are calculated relative to an underlying sample of point sources that are detected in the required selection bands and pass our data quality and photometric error cuts. We conduct our analyses at two magnitude limits, i85% for both i-band magnitude limits and efficiencies of >80% to the bright limit and >60% to the faint limit; however, the giW1 and giW1+variability methods give the highest quasar surface densities. The XDQSOz method and combinations of W1W2/giW1/XDQSOz with variability are among the better selection methods when both high completeness and high efficiency are desired. We also present the OzDES Quasar Catalog of 1263 spectroscopically confirmed quasars from three years of OzDES observation in the 30 deg2 of the DES supernova fields. The catalog includes quasars with redshifts up to z4 and brighter than i = 22 mag, although the catalog is not complete up to this magnitude limit.

Chemically peculiar stars in dwarf galaxies provide a window for exploring the birth environment of stars with varying chemical enrichment. We present a chemical abundance analysis of the brightest star in the newly discovered ultra-faint dwarf galaxy candidate Tucana III. Because it is particularly bright for a star in an ultra-faint Milky Way (MW) satellite, we are able to measure the abundance of 28 elements, including 13 neutron-capture species. This star, DES J235532.66−593114.9 (DES J235532), shows a mild enhancement in neutron-capture elements associated with the r-process and can be classified as an r-I star. DES J235532 is the first r-I star to be discovered in an ultra-faint satellite, and Tuc III is the second extremely low-luminosity system found to contain rprocess enriched material, after Reticulum II. Comparison of the abundance pattern of DES J235532 with r-I and r-II stars found in other dwarf galaxies and in the MW halo suggests a common astrophysical origin for the neutron-capture elements seen in all r-process enhanced stars. We explore both internal and external scenarios for the r-process enrichment of Tuc III and show that with abundance patterns for additional stars, it should be possible to distinguish between them.

We present Magellan/IMACS spectroscopy of the recently discovered Milky Way satellite TucanaIII (Tuc III). We identify 26 member stars in TucIII from which we measure a mean radial velocity of vhel=−102.3±0.4 (stat.)±2.0(sys.) km s-1, a velocity dispersion of - 0.1+0.1 0.7 km s-1, and a mean metallicity of = - - [Fe/H] 2.42+0.08 0.07. The upper limit on the velocity dispersion is σ

We address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23.

The Dark Energy Camera has captured a large set of images as part of Science Verification (SV) for the Dark Energy Survey (DES). The SV footprint covers a large portion of the outer LargeMagellanic Cloud (LMC), providing photometry 1.5 mag fainter than the main sequence turn-off of the oldest LMC stellar population.We derive geometrical and structural parameters for various stellar populations in the LMC disc. For the distribution of all LMC stars, we find an inclination of i = −38. ◦ 14 ± 0. ◦ 08 (near side in the north) and a position angle for the line of nodes of θ0 = 129. ◦ 51 ± 0. ◦ 17. We find that stars younger than ∼4 Gyr are more centrally concentrated than older stars. Fitting a projected exponential disc shows that the scale radius of the old populations is R>4 Gyr = 1.41 ± 0.01 kpc, while the younger population has R

We present spectroscopic confirmation of two new gravitationally lensed quasars, discovered in the Dark Energy Survey (DES) and Wide-field Infrared Survey Explorer (WISE) based on their multiband photometry and extended morphology in DES images. Images of DES J0115−5244 show a red galaxy with two blue point sources at either side, which are images of the same quasar at zs = 1.64 as obtained by our long-slit spectroscopic data. The Einstein radius estimated from the DES images is 0.51 arcsec. DES J2146−0047 is in the area of overlap between DES and the Sloan Digital Sky Survey (SDSS). Two blue components are visible in the DES and SDSS images. The SDSS fibre spectrum shows a quasar component at zs = 2.38 and absorption by Mg II and Fe II at zl = 0.799, which we tentatively associate with the foreground lens galaxy. Our long-slit spectra show that the blue components are resolved images of the same quasar. The Einstein radius is 0.68 arcsec, corresponding to an enclosed mass of 1.6 × 1011M . Three other candidates were observed and rejected, two being low-redshift pairs of starburst galaxies, and one being a quasar behind a blue star. These first confirmation results provide an important empirical validation of the data mining and model-based selection that is being applied to the entire DES data set.

The Dark Energy Survey (DES) is a 5000 sq deg griz imaging survey to be conducted using a proposed 3 sq deg (2.2deg-diameter) wide-field mosaic camera on the CTIO Blanco 4m telescope. The primary scientific goal of the DES is to constrain dark energy cosmological parameters via four complementary methods: galaxy cluster counting, weak lensing, galaxy angular correlations, and Type Ia supernovae, supported by precision photometric redshifts. Here we present the photometric calibration plans for the DES, including a discussion of standard stars and field-to-field calibrations., 14 pages, 7 figures, to appear in the proceedings for the workshop, "The Future of Photometric, Spectrophotometric, and Polarimetric Standardization"