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We present cosmological results from a combined analysis of galaxy clustering and weak gravitational lensing, using 1321 deg 2 of griz imaging data from the first year of the Dark Energy Survey (DES Y1). We combine three two-point functions: (i) the cosmic shear correlation function of 26 million source galaxies in four redshift bins, (ii) the galaxy angular autocorrelation function of 650,000 luminous red galaxies in five redshift bins, and (iii) the galaxy-shear cross-correlation of luminous red galaxy positions and source galaxy shears. To demonstrate the robustness of these results, we use independent pairs of galaxy shape, photometric redshift estimation and validation, and likelihood analysis pipelines. To prevent confirmation bias, the bulk of the analysis was carried out while "blind" to the true results; we describe an extensive suite of systematics checks performed and passed during this blinded phase. The data are modeled in flat ΛCDM and wCDM cosmologies, marginalizing over 20 nuisance parameters, varying 6 (for ΛCDM) or 7 (for wCDM) cosmological parameters including the neutrino mass density and including the 457 × 457 element analytic covariance matrix. We find consistent cosmological results from these three two-point functions, and from their combination obtain S8 ≡ σ8(Ωm/0.3) 0.5 = 0.773 +0.026 −0.020 and Ωm = 0.267 +0.030 −0.017 for ΛCDM; for wCDM, we find S8 = 0.782 +0.036 −0.024 , Ωm = 0.284 +0.033 −0.030 , and w = −0.82 +0.

We describe redMaPPer, a new red-sequence cluster finder specifically designed to make optimal use of ongoing and near-future large photometric surveys. The algorithm has multiple attractive features: (1) It can iteratively self-train the red-sequence model based on a minimal spectroscopic training sample, an important feature for high redshift surveys; (2) It can handle complex masks with varying depth; (3) It produces cluster-appropriate random points to enable large-scale structure studies; (4) All clusters are assigned a full redshift probability distribution P (z); (5) Similarly, clusters can have multiple candidate central galaxies, each with corresponding centering probabilities; (6) The algorithm is parallel and numerically efficient: it can run a Dark Energy Survey-like catalog in ∼ 500 CPU hours; (7) The algorithm exhibits excellent photometric redshift performance, the richness estimates are tightly correlated with external mass proxies, and the completeness and purity of the corresponding catalogs is superb. We apply the redMaPPer algorithm to ∼ 10,000 deg 2 of SDSS DR8 data, and present the resulting catalog of ∼ 25,000 clusters over the redshift range z ∈ [0.08,0.55]. The redMaPPer photometric redshifts are nearly Gaussian, with a scatter σ z ≈ 0.006 at z ≈ 0.1, increasing to σ z ≈ 0.02 at z ≈ 0.5 due to increased photometric noise near the survey limit. The median value for |∆z|/(1 + z) for the full sample is 0.006. The incidence of projection effects is low (≤ 5%). Detailed performance comparisons of the redMaPPer DR8 cluster catalog to X-ray and SZ catalogs are presented in a companion paper.

We present UV, optical, and near-infrared (NIR) photometry of the first electromagnetic counterpart to a gravitational wave source from Advanced Laser Interferometer Gravitational-wave Observatory (LIGO)/Virgo, the binary neutron star merger GW170817. Our data set extends from the discovery of the optical counterpart at 0.47-18.5 days post-merger, and includes observations with the Dark Energy Camera (DECam), Gemini-South/ FLAMINGOS-2 (GS/F2), and the Hubble Space Telescope (HST). The spectral energy distribution (SED) inferred from this photometry at 0.6 days is well described by a blackbody model with » T 8300 K, a radius of »Ŕ 4.5 10 14 cm (corresponding to an expansion velocity of » v c 0.3 ), and a bolometric luminosity of »Ĺ 5 10 bol 41 erg s −1 . At 1.5 days we find a multi-component SED across the optical and NIR, and subsequently we observe rapid fading in the UV and blue optical bands and significant reddening of the optical/ NIR colors. Modeling the entire data set, we find that models with heating from radioactive decay of 56 Ni, or those with only a single component of opacity from r-process elements, fail to capture the rapid optical decline and red optical/NIR colors. Instead, models with two components consistent with lanthanide-poor and lanthanide-rich ejecta provide a good fit to the data; the resulting "blue" component has » . These ejecta masses are broadly consistent with the estimated r-process production rate required to explain the Milky Way r-process abundances, providing the first evidence that binary neutron star (BNS) mergers can be a dominant site of r-process enrichment.

We use 26 × 10 6 galaxies from the Dark Energy Survey (DES) Year 1 shape catalogs over 1321 deg 2 of the sky to produce the most significant measurement of cosmic shear in a galaxy survey to date. We constrain cosmological parameters in both the flat ΛCDM and the wCDM models, while also varying the neutrino mass density. These results are shown to be robust using two independent shape catalogs, two independent photo-z calibration methods, and two independent analysis pipelines in a blind analysis. We find a 3.5% fractional uncertainty on σ 8 ðΩ m =0.3Þ 0.5 ¼ 0.782 −0.39 . We find results that are consistent with previous cosmic shear constraints in σ 8 -Ω m , and we see no evidence for disagreement of our weak lensing data with data from the cosmic microwave background. Finally, we find no evidence preferring a wCDM model allowing w ≠ −1. We expect further significant improvements with subsequent years of DES data, which will more than triple the sky coverage of our shape catalogs and double the effective integrated exposure time per galaxy.

We search for excess γ-ray emission coincident with the positions of confirmed and candidate Milky Way satellite galaxies using six years of data from the Fermi Large Area Telescope (LAT). Our sample of 45 stellar systems includes 28 kinematically confirmed dark-matter-dominated dwarf spheroidal galaxies (dSphs) and 17 recently discovered systems that have photometric characteristics consistent with the population of known dSphs. For each of these targets, the relative predicted γ-ray flux due to dark matter annihilation is taken from kinematic analysis if available, and estimated from a distance-based scaling relation otherwise, assuming that the stellar systems are DM-dominated dSphs. LAT data coincident with four of the newly discovered targets show a slight preference (each 2σ local) for γ-ray emission in excess of the background. However, the ensemble of derived γ-ray flux upper limits for individual targets is consistent with the expectation from analyzing random blank-sky regions, and a combined analysis of the population of stellar systems yields no globally significant excess (global significance ). Our analysis has increased sensitivity compared to the analysis of 15 confirmed dSphs by Ackermann et al. The observed constraints on the DM annihilation cross section are statistically consistent with the background expectation, improving by a factor of ∼2 for large DM masses ( and ) and weakening by a factor of ∼1.5 at lower masses relative to previously observed limits.

With the Sixth Data Release of the Sloan Digital Sky Survey, the imaging of the Northern Galactic Cap is now complete. The survey contains images and parameters of roughly 287 million objects over 9583 deg^2, and 1.27 million spectra of stars, galaxies, quasars and blank sky (for sky subtraction) selected over 7425 deg^2. This release includes much more extensive stellar spectroscopy than previously, and also includes detailed estimates of stellar temperatures, gravities, and metallicities. The results of improved photometric calibration are now available, with uncertainties of roughly 1% in g, r, i, and z, and 2% in u, substantially better than the uncertainties in previous data releases. The spectra in this data release have improved wavelength and flux calibration, especially in the extreme blue and extreme red, leading to the qualitatively better determination of stellar types and radial velocities. The spectrophotometric fluxes are now tied to point spread function magnitudes of stars rather than fiber magnitudes, giving a 0.35 mag change in the spectrophotometric flux scale. Systematic errors in the velocity dispersions of galaxies have been fixed, and the results of two independent codes for determining spectral classifications and redshifts are made available. (Abridged)Comment: 21 pages with 8 color figures. ApJS, in press. Minor modifications from previous versio

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.