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.

Using data from the COSMOS survey, we perform the first joint analysis of galaxy-galaxy weak lensing, galaxy spatial clustering, and galaxy number densities. Carefully accounting for sample variance and for scatter between stellar and halo mass, we model all three observables simultaneously using a novel and self-consistent theoretical framework. Our results provide strong constraints on the shape and redshift evolution of the stellar-to-halo mass relation (SHMR) from z = 0.2 to z = 1. At low stellar mass, we find that halo mass scales as M h ∝ M 0.46 * and that this scaling does not evolve significantly with redshift from z = 0.2 to z = 1. The slope of the SHMR rises sharply at M * > 5 × 10 10 M ⊙ and as a consequence, the stellar mass of a central galaxy becomes a poor tracer of its parent halo mass. We show that the dark-to-stellar ratio, M h /M * , varies from low to high masses, reaching a minimum of M h /M * ∼ 27 at M * = 4.5 × 10 10 M ⊙ and M h = 1.2 × 10 12 M ⊙ . This minimum is important for models of galaxy formation because it marks the mass at which the accumulated stellar growth of the central galaxy has been the most efficient. We describe the SHMR at this minimum in terms of the "pivot stellar mass", M piv * , the "pivot halo mass", M piv h , and the "pivot ratio", (M h /M * ) piv . Thanks to a homogeneous analysis of a single data set spanning a large redshift range, we report the first detection of mass downsizing trends for both M piv h and M piv * . The pivot stellar mass decreases from M piv * = 5.75±0.13×10 10 M ⊙ at z = 0.88 to M piv * = 3.55±0.17×10 10 M ⊙ at z = 0.37. Intriguingly, however, the corresponding evolution of M piv h leaves the pivot ratio constant with redshift at (M h /M * ) piv ∼ 27. We use simple arguments to show how this result raises the possibility that star formation quenching may ultimately depend on M h /M * and not simply M h , as is commonly assumed. We show that simple models with such a dependence naturally lead to downsizing in the sites of star formation. Finally, we discuss the implications of our results in the context of popular quenching models, including disk instabilities and AGN feedback.

The Blanco Cosmology Survey is 4-band (griz) optical-imaging survey that covers ∼80 deg 2 of the southern sky. The survey consists of two fields roughly centered at (RA,DEC) = (23h,-55d) and (5h30m,-53d) with imaging designed to reach depths sufficient for the detection of L galaxies out to a redshift of one. In this paper we describe the reduction of the survey data, the creation of calibrated source catalogs and a new method for the separation of stars and galaxies. We search these catalogs for galaxy clusters at z ≤0.75 by identifying spatial over-densities of red-sequence galaxies. We report the coordinates, redshift, and optical richness, λ, for 764 detected galaxy clusters at z ≤ 0.75. This sample, >85% of which are new discoveries, has a median redshift of 0.52 and median richness λ(0.4L ) of 16.4. Accompanying this paper we also release data products including the reduced images and calibrated source catalogs. These products are available at http://data. rcc.uchicago.edu/dataset/blanco-cosmology-survey.

We present a precise estimate of the bulk virial scaling relation of halos formed via hierarchical clustering in an ensemble of simulated cold dark matter cosmologies. The result is insensitive to cosmological parameters, the presence of a trace, dissipationless gas component, and numerical resolution down to a limit of ∼ 1000 particles. The dark matter velocity dispersion scales with total mass as log(σ DM (M, z)) = log(1082.9 ± 4.0 km s −1 ) + (0.3361 ± 0.0026) log(h(z)M 200 /10 15 M ⊙ ), with h(z) the dimensionless Hubble parameter. At fixed mass, the velocity dispersion likelihood is nearly log-normal, with scatter σ ln σ = 0.0426 ± 0.015, except for a tail to higher dispersions containing 10% of the population that are merger transients. We combine this relation with the halo mass function in ΛCDM models, and show that a low normalization condition, S 8 = σ 8 (Ω m /0.3) 0.35 = 0.69, favored by recent WMAP and SDSS analysis requires that galaxy and gas specific energies in rich clusters be 50% larger than that of the underlying dark matter. Such large energetic biases are in conflict with the current generation of direct simulations of cluster formation. A higher normalization, S 8 = 0.80, alleviates this tension and implies that the hot gas fraction within r 500 is (0.71 ± 0.09)h −3/2 70 Ω b /Ω m , a value consistent with recent Sunyaev-Zel'dovich observations.

We present a new algorithm for generating merger trees and halo catalogs which explicitly ensures consistency of halo properties (mass, position, and velocity) across timesteps. Our algorithm has demonstrated the ability to improve both the completeness (through detecting and inserting otherwise missing halos) and purity (through detecting and removing spurious objects) of both merger trees and halo catalogs. In addition, our method is able to robustly measure the self-consistency of halo finders; it is the first to directly measure the uncertainties in halo positions, halo velocities, and the halo mass function for a given halo finder based on consistency between snapshots in cosmological simulations. We use this algorithm to generate merger trees for two large simulations (Bolshoi and Consuelo) and evaluate two halo finders (ROCKSTAR and BDM). We find that both the ROCKSTAR and BDM halo finders track halos extremely well; in both, the number of halos which do not have physically consistent progenitors is at the 1-2% level across all halo masses. Our code is publicly available at

We present a large catalog of optically selected galaxy clusters from the application of a new Gaussian Mixture Brightest Cluster Galaxy (GMBCG) algorithm to SDSS Data Release 7 data. The algorithm detects clusters by identifying the red sequence plus Brightest Cluster Galaxy (BCG) feature, which is unique for galaxy clusters and does not exist among field galaxies. Red sequence clustering in color space is detected using an Error Corrected Gaussian Mixture Model. We run GMBCG on 8240 square degrees of photometric data from SDSS DR7 to assemble the largest ever optical galaxy cluster catalog, consisting of over 55,000 rich clusters across the redshift range from 0.1 < z < 0.55. We present Monte Carlo tests of completeness and purity and perform cross-matching with X-ray clusters and with the maxBCG sample at low redshift. These tests indicate high completeness and purity across the full redshift range for clusters with 15 or more members. The catalog can be accessed from the following website:a Although the 4000Åbreak starts shifting into SDSS r band at z ∼ 0.36, we observed that g − r color is still better than r − i color for detecting red sequence up to redshift 0.43.

Understanding the mechanisms that lead dense environments to host galaxies with redder colors, more spheroidal morphologies, and lower star formation rates than field populations remains an important problem. As most candidate processes ultimately depend on host halo mass, accurate characterizations of the local environment, ideally tied to halo mass estimates and spanning a range in halo mass and redshift are needed. In this work, we present and test a rigorous, probabalistic method for assigning galaxies to groups based on precise photometric redshifts and X-ray selected groups drawn from the COSMOS field. The groups have masses in the range 10 13 M 200c /M 10 14 and span redshifts 0 < z < 1. We characterize our selection algorithm via tests on spectroscopic subsamples, including new data obtained at the VLT, and by applying our method to detailed mock catalogs. We find that our group member galaxy sample has a purity of 84% and completeness of 92% within 0.5R 200c . We measure the impact of uncertainties in redshifts and group centering on the quality of the member selection with simulations based on current data as well as future imaging and spectroscopic surveys. As a first application of our new group member catalog which will be made publicly available, we show that member galaxies exhibit a higher quenched fraction compared to the field at fixed stellar mass out to z ∼ 1, indicating a significant relationship between star formation and environment at group scales. We also address the suggestion that dusty star forming galaxies in such groups may impact the high-power spectrum of the cosmic microwave background and find that such a population cannot explain the low power seen in recent SZ measurements.