The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.

We study the orientations of satellite galaxies in redMaPPer clusters constructed from the Sloan Digital Sky Survey at 0.1 < z < 0.35 to determine whether there is any preferential tendency for satellites to point radially towards cluster centres. We analyse the satellite alignment (SA) signal based on three shape measurement methods (re-Gaussianization, de Vaucouleurs, and isophotal shapes), which trace galaxy light profiles at different radii. The measured SA signal depends on these shape measurement methods. We detect the strongest SA signal in isophotal shapes, followed by de Vaucouleurs shapes. While no net SA signal is detected using re-Gaussianization shapes across the entire sample, the observed SA signal reaches a statistically significant level when limiting to a subsample of higher luminosity satellites. We further investigate the impact of noise, systematics, and real physical isophotal twisting effects in the comparison between the SA signal detected via different shape measurement methods. Unlike previous studies, which only consider the dependence of SA on a few parameters, here we explore a total of 17 galaxy and cluster properties, using a statistical model averaging technique to naturally account for parameter correlations and identify significant SA predictors. We find that the measured SA signal is strongest for satellites with the following characteristics: higher luminosity, smaller distance to the cluster centre, rounder in shape, higher bulge fraction, and distributed preferentially along the major axis directions of their centrals. Finally, we provide physical explanations for the identified dependences and discuss the connection to theories of SA.

We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 deg(2) contiguous patch of DES data from the Science Verification (SV) period of observations. Using large-scale measurements, we constrain the matter density of the Universe as Omega(m) = 0.31 +/- 0.09 and the clustering amplitude of the matter power spectrum as sigma(8) = 0.74 +/- 0.13 after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into S-8 = sigma(8)(Omega(m)/0.3)(0.16) = 0.74 +/- 0.12 for our fiducial lens redshift bin at 0.35 < z < 0.5, while S-8 = 0.78 +/- 0.09 using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck Cosmic Microwave Background data, baryon accoustic oscillations and Supernova Type Ia measurements.

The potential of using cluster clustering for calibrating the mass-richness relation of galaxy clusters has been recognized theoretically for over a decade. Here, we demonstrate the feasibility of this technique to achieve high-precision mass calibration using redMaPPer clusters in the Sloan Digital Sky Survey North Galactic Cap. By including cross-correlations between several richness bins in our analysis, we significantly improve the statistical precision of our mass constraints. The amplitude of the mass-richness relation is constrained to 7 per cent statistical precision by our analysis. However, the error budget is systematics dominated, reaching a 19 per cent total error that is dominated by theoretical uncertainty in the bias-mass relation for dark matter haloes. We confirm the result from Miyatake et al. that the clustering amplitude of redMaPPer clusters depends on galaxy concentration as defined therein, and we provide additional evidence that this dependence cannot be sourced by mass dependences: some other effect must account for the observed variation in clustering amplitude with galaxy concentration. Assuming that the observed dependence of redMaPPer clustering on galaxy concentration is a form of assembly bias, we find that such effects introduce a systematic error on the amplitude of the mass-richness relation that is comparable to the error bar from statistical noise. The results presented here demonstrate the power of cluster clustering for mass calibration and cosmology provided the current theoretical systematics can be ameliorated.

We detect the kinematic Sunyaev-Zel'dovich (kSZ) effect with a statistical significance of 4.2 sigma by combining a cluster catalogue derived from the first year data of the Dark Energy Survey with cosmic microwave background temperature maps from the South Pole Telescope Sunyaev-Zel'dovich Survey. This measurement is performed with a differential statistic that isolates the pairwise kSZ signal, providing the first detection of the large-scale, pairwise motion of clusters using redshifts derived from photometric data. By fitting the pairwise kSZ signal to a theoretical template, we measure the average central optical depth of the cluster sample, (tau) over bar (e) = (3.75 +/- 0.89) x 10(-3). We compare the extracted signal to realistic simulations and find good agreement with respect to the signal to noise, the constraint on (tau) over bar (e), and the corresponding gas fraction. High-precision measurements of the pairwise kSZ signal with future data will be able to place constraints on the baryonic physics of galaxy clusters, and could be used to probe gravity on scales greater than or similar to 100 Mpc.

In cosmological N-body simulations, the representation of dark matter as discrete 'macroparticles' suppresses the growth of structure, such that simulations no longer reproduce linear theory on small scales near k(Nyquist). Marcos et al. demonstrate that this is due to sparse sampling of modes near k(Nyquist) and that the often-assumed continuum growing modes are not proper growing modes of the particle system. We develop initial conditions (ICs) that respect the particle linear theory growing modes and then rescale the mode amplitudes to account for growth suppression. These ICs also allow us to take advantage of our very accurate N-body code ABACUS to implement second-order Lagrangian perturbation theory (2LPT) in configuration space. The combination of 2LPT and rescaling improves the accuracy of the late-time power spectra, halo mass functions, and halo clustering. In particular, we achieve 1 per cent accuracy in the power spectrum down to k(Nyquist), versus k(Nyquist)/4 without rescaling or k(Nyquist)/13 without 2LPT, relative to an oversampled reference simulation. We anticipate that our 2LPT will be useful for large simulations where fast Fourier transforms are expensive and that rescaling will be useful for suites of medium-resolution simulations used in cosmic emulators and galaxy survey mock catalogues. Code to generate ICs is available at https://github.com/lgarrison/zeldovich-PLT.

Cosmic voids are usually identified in spectroscopic galaxy surveys, where 3D information about the large-scale structure of the Universe is available. Although an increasing amount of photometric data is being produced, its potential for void studies is limited since photometric redshifts induce line-of-sight position errors of >= 50 Mpc h(-1)which can render many voids undetectable. We present a new void finder designed for photometric surveys, validate it using simulations, and apply it to the high-quality photo-z redMaGiC galaxy sample of the DES Science Verification data. The algorithm works by projecting galaxies into 2D slices and finding voids in the smoothed 2D galaxy density field of the slice. Fixing the line-of-sight size of the slices to be at least twice the photo-z scatter, the number of voids found in simulated spectroscopic and photometric galaxy catalogues is within 20 per cent for all transverse void sizes, and indistinguishable for the largest voids (R-v >= 70 Mpc h(-1)). The positions, radii, and projected galaxy profiles of photometric voids also accurately match the spectroscopic void sample. Applying the algorithm to the DES-SV data in the redshift range 0.2 < z < 0.8, we identify 87 voids with comoving radii spanning the range 18-120 Mpc h(-1), and carry out a stacked weak lensing measurement. With a significance of 4.4 sigma, the lensing measurement confirms that the voids are truly underdense in the matter field and hence not a product of Poisson noise, tracer density effects or systematics in the data. It also demonstrates, for the first time in real data, the viability of void lensing studies in photometric surveys.

We present a cosmic microwave background (CMB) lensing map produced from a linear combination of South Pole Telescope (SPT) and Planck temperature data. The 150 GHz temperature data from the 2500 deg(2) SPT-SZ survey is combined with the Planck 143 GHz data in harmonic space to obtain a temperature map that has a broader l coverage and less noise than either individual map. Using a quadratic estimator technique on this combined temperature map, we produce a map of the gravitational lensing potential projected along the line of sight. We measure the auto-spectrum of the lensing potential C-L(phi phi), and compare it to the theoretical prediction for a.CDM cosmology consistent with the Planck 2015 data set, finding a best-fit amplitude of 0.95(-0.06)(+0.06) (stat.)(-0.01)(+0.01)+ (sys.). The null hypothesis of no lensing is rejected at a significance of 24 sigma. One important use of such a lensing potential map is in cross-correlations with other dark matter tracers. We demonstrate this cross-correlation in practice by calculating the cross-spectrum, C-L(phi) G, between the SPT+ Planck lensing map and Wide-field Infrared Survey Explorer (WISE) galaxies. We fit C-L(phi G) to a power law of the form p(L) = a(L/L-0)(-b) with a, L-0, and b fixed, and find eta(phi G) = C-L(phi G)/p(L) = 0.94(-0.04)(+0.04), which is marginally lower, but in good agreement with eta(phi G) = 1.00-(+0.02)(0.01), the best-fit amplitude for the cross-correlation of Planck-2015 CMB lensing and WISE galaxies over similar to 67% of the sky. The lensing potential map presented here will be used for cross-correlation studies with the Dark Energy Survey, whose footprint nearly completely covers the SPT 2500 deg(2) field.

We present a comparison between several observational tests of the post-reionization intergalactic medium and the numerical simulations of reionization completed under the Cosmic Reionization On Computers (CROC) project. The CROC simulations match the gap distribution reasonably well, and also provide a good match for the distribution of peak heights, but there is a notable lack of wide peaks in the simulated spectra and the flux-probability distribution functions are poorly matched in the narrow redshift interval 5.5 < z < 5.7, with the match at other redshifts being significantly better, albeit not exact. Both discrepancies are related: simulations show more opacity than the data.

Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES-SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES-SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.