On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ∼ 1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40 − 8 + 8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 M ⊙ . An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ∼ 40 Mpc ) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ∼ 9 and ∼ 16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.

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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 describe the Sloan