D. A. Goldstein

The RedMaPPer Galaxy Cluster Catalog From DES Science Verification Data

We describe updates to the redMaPPer algorithm, a photometric red-sequence cluster finder specifically designed for large photometric surveys. The updated algorithm is applied to 150 deg(2) of Science Verification (SV) data from the Dark Energy Survey (DES), and to the Sloan Digital Sky Survey (SDSS) DR8 photometric data set. The DES SV catalog is locally volume limited and contains 786 clusters with richness lambda > 20 (roughly equivalent to M500c greater than or similar to 10(14) h(70)(-1)M(circle dot)) and 0.2 < z < 0.9. The DR8 catalog consists of 26,311 clusters with 0.08 < z < 0.6, with a sharply increasing richness threshold as a function of redshift for z greater than or similar to 0.35. The photometric redshift performance of both catalogs is shown to be excellent, with photometric redshift uncertainties controlled at the sigma(z)/(1+ z) similar to 0.01 level for z greater than or similar to 0.7, rising to similar to 0.02 at z similar to 0.9 in DES SV. We make use of Chandra and XMM X-ray and South Pole Telescope Sunyaev-Zeldovich data to show that the centering performance and mass-richness scatter are consistent with expectations based on prior runs of redMaPPer on SDSS data. We also show how the redMaPPer photo-z and richness estimates are relatively insensitive to imperfect star/galaxy separation and small-scale star masks.

Automated transient identification in the Dark Energy Survey

We describe an algorithm for identifying point-source transients and moving objects on reference-subtracted optical images containing artifacts of processing and instrumentation. The algorithm makes use of the supervised machine learning technique known as Random Forest. We present results from its use in the Dark Energy Survey Supernova program (DES-SN), where it was trained using a sample of 898,963 signal and background events generated by the transient detection pipeline. After reprocessing the data collected during the first DES-SN observing season (2013 September through 2014 February) using the algorithm, the number of transient candidates eligible for human scanning decreased by a factor of 13.4, while only 1.0% of the artificial Type Ia supernovae (SNe) injected into search images to monitor survey efficiency were lost, most of which were very faint events. Here we characterize the algorithms performance in detail, and we discuss how it can inform pipeline design decisions for future time-domain imaging surveys, such as the Large Synoptic Survey Telescope and the Zwicky Transient Facility. An implementation of the algorithm and the training data used in this paper are available at at http://portal.nersc.gov/project/dessn/autoscan.

COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses

This work is supported by the Swiss National Science Foundation (SNSF). S. H. Suyu and D. C. Y. Chao thank the Max Planck Society for support through the Max Planck Research Group for SHS. T. Treu acknowledges support by the National Science Foundation through grant 1450141, by the Packard Foundation through a Packard Research Fellowship and by the UCLA Dean of Physical Sciences. K. Rojas is supported by Becas de Doctorado Nacional CONICYT 2017. T. Anguita and M. Chijani acknowledge support by proyecto FONDECYT 11130630 and by the Ministry for the Economy, Development, and Tourism’s Programa Inicativa Cientifica Milenio through grant IC 12009, awarded to The Millennium Institute of Astrophysics (MAS). M. Tewes acknowledges support from the DFG grant Hi 1495/2-1. J. Garcia-Bellido is supported by the Research Project FPA2015-68048 [MINECO-FEDER], and the Centro de Excelencia Severo Ochoa Program SEV-2012-0249. C. D. Fassnacht acknowledges support from the National Science Foundation grant AST-1312329 and from the UC Davis Physics Department and Dean of Math and Physical Sciences. Funding for the DES Projects has been provided by the US Department of Energy, the US National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, the Center for Cosmology and Astro-Particle Physics at the Ohio State University, the Mitchell Institute for Fundamental Physics and Astronomy at Texas A&M University, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and the Ministerio da Ciencia, Tecnologia e Inovacao, the Deutsche Forschungsgemeinschaft and the Collaborating Institutions in the Dark Energy Survey ... The DES data management system is supported by the National Science Foundation under Grant Number AST-1138766. The DES participants from Spanish institutions are partially supported by MINECO under grants AYA2015-71825, ESP2015-88861, FPA2015-68048, SEV-2012-0234, SEV-2012-0249, and MDM-2015-0509, some of which include ERDF funds from the European Union. IFAE is partially funded by the CERCA programme of the Generalitat de Catalunya.

Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data

Shear peak statistics has gained a lot of attention recently as a practical alternative to the two-point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg² field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range 0 4 would require significant corrections, which is why we do not include them in our analysis. We compare our results to the cosmological constraints from the two-point analysis on the SV field and find them to be in good agreement in both the central value and its uncertainty. We discuss prospects for future peak statistics analysis with upcoming DES data.

VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

FO is supported jointly by CAPES (the Science without Borders programme) and the Cambridge Commonwealth Trust. RGM, CAL, MWA, MB, SLR acknowledge the support of UK Science and Technology Research Council (STFC). AJC acknowledges the support of a Raymond and Beverly Sackler visiting fellowship at the Institute of Astronomy. For further information regarding funding please visit the publishers website.

Farthest neighbor: the distant Milky Way satellite Eridanus II*

We present Magellan/IMACS spectroscopy of the recently discovered Milky Way satellite Eridanus II (Eri II). We identify 28 member stars in Eri II, from which we measure a systemic radial velocity of nu(hel)= 75.6 +/- 1.3(stat.) +/- 2.0 (sys.) km s(-1) and a velocity dispersion of 6.9(-0.9)(+1.2) km s(-1). Assuming that Eri. II is a dispersion-supported system in dynamical equilibrium, we derive a mass within the half-light radius of 1.2(-0.3)(+0.4) x 10(7) M-circle dot, indicating a mass-tolight ratio of 420(-140)(+210) M-circle dot/L-circle dot and confirming that it is a dark matter-dominated dwarf galaxy. From the equivalent width measurements of the Ca triplet lines of 16 red giant member stars, we derive a mean metallicity of [ Fe/H] = -2.38 +/- 0.13 and a metallicity dispersion of sigma[Fe/H]= 0.47(-0.09)(+0.12). The velocity of Eri. II in the Galactic standard of rest frame is nu(GSR) = -66.6 km s(-1), indicating that either Eri. II is falling into the Milky Way potential for the first time or that it has passed the apocenter of its orbit on a subsequent passage. At a Galactocentric distance of similar to 370 kpc, Eri II is one of the Milky Ways most distant satellites known. Additionally, we show that the bright blue stars previously suggested to be a young stellar population are not associated with Eri. II. The lack of gas and recent star formation in Eri II is surprising given its mass and distance from the Milky Way, and may place constraints on models of quenching in dwarf galaxies and on the distribution of hot gas in the Milky Way halo. Furthermore, the large velocity dispersion of Eri II can be combined with the existence of a central star cluster to constrain massive compact halo object dark matter with mass greater than or similar to 10 M-circle dot.

Cross-correlation of gravitational lensing from DES Science Verification data with SPT and Planck lensing

We measure the cross-correlation between weak lensing of galaxy images and of the cosmic microwave background (CMB). The effects of gravitational lensing on different sources will be correlated if the lensing is caused by the same mass fluctuations. We use galaxy shape measurements from 139 deg(2) of the Dark Energy Survey (DES) Science Verification data and overlapping CMB lensing from the South Pole Telescope (SPT) and Planck. The DES source galaxies have a median redshift of z(med) similar to 0.7, while the CMB lensing kernel is broad and peaks at z similar to 2. The resulting cross-correlation is maximally sensitive to mass fluctuations at z similar to 0.44. Assuming the Planck 2015 best-fitting cosmology, the amplitude of the DESxSPT cross-power is found to be A(SPT) = 0.88 +/- 0.30 and that from DESxPlanck to be A(Planck) = 0.86 +/- 0.39, where A = 1 corresponds to the theoretical prediction. These are consistent with the expected signal and correspond to significances of 2.9 sigma and 2.2 sigma, respectively. We demonstrate that our results are robust to a number of important systematic effects including the shear measurement method, estimator choice, photo-z uncertainty and CMB lensing systematics. We calculate a value of A = 1.08 +/- 0.36 for DESxSPT when we correct the observations with a simple intrinsic alignment model. With three measurements of this cross-correlation now existing in the literature, there is not yet reliable evidence for any deviation from the expected LCDM level of cross-correlation. We provide forecasts for the expected signal-to-noise ratio of the combination of the five-year DES survey and SPT-3G.

Galaxy bias from the Dark Energy Survey Science Verification data: Combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ˜116 deg2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1sigma error bars in four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2-0.4), 0.97 ± 0.15 (z = 0.4-0.6), 1.38 ± 0.39 (z = 0.6-0.8), and 1.45 ± 0.56 (z = 0.8-1.0). These measurements are consistent at the 2sigma level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1sigma error bars. In addition, our method provides the only sigma8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

Discovery of the Lensed Quasar System DES J0408-5354

We report the discovery and spectroscopic confirmation of the quad-like lensed quasar system DES J0408-5354 found in the Dark Energy Survey (DES) Year 1 (Y1) data. This system was discovered during a search for DES Y1 strong lensing systems using a method that identified candidates as red galaxies with multiple blue neighbors. DES J0408-5354 consists of a central red galaxy surrounded by three bright (i < 20) blue objects and a fourth red object. Subsequent spectroscopic observations using the Gemini South telescope confirmed that the three blue objects are indeed the lensed images of a quasar with redshift z = 2.375, and that the central red object is an early-type lensing galaxy with redshift z = 0.597. DES J0408-5354 is the first quad lensed quasar system to be found in DES and begins to demonstrate the potential of DES to discover and dramatically increase the sample size of these very rare objects.

Imprint of DES superstructures on the cosmic microwave background

Small temperature anisotropies in the cosmic microwave background (CMB) can be sourced by density perturbations via the late-time integrated Sachs-Wolfe (ISW) effect. Large voids and superclusters are excellent environments to make a localized measurement of this tiny imprint. In some cases excess signals have been reported. We probed these claims with an independent data set, using the first year data of the Dark Energy Survey (DES) in a different footprint, and using a different superstructure finding strategy. We identified 52 large voids and 102 superclusters at redshifts 0.2 < z < 0.65. We used the Jubilee simulation to a priori evaluate the optimal ISW measurement configuration for our compensated top-hat filtering technique, and then performed a stacking measurement of the CMB temperature field based on the DES data. For optimal configurations, we detected a cumulative cold imprint of voids with DeltaTf ≈ -5.0 ± 3.7 muK and a hot imprint of superclusters DeltaTf ≈ 5.1 ± 3.2 muK; this is ˜1.2sigma higher than the expected |DeltaTf| ≈ 0.6 muK imprint of such superstructures in Lambda cold dark matter (LambdaCDM). If we instead use an a posteriori selected filter size (R/Rv = 0.6), we can find a temperature decrement as large as DeltaTf ≈ -9.8 ± 4.7 muK for voids, which is ˜2sigma above LambdaCDM expectations and is comparable to previous measurements made using Sloan Digital Sky Survey superstructure data.