J. Prat

Galaxy-galaxy lensing in the Dark Energy Survey Science Verification data

We present galaxy-galaxy lensing results from 139 deg(2) of Dark Energy Survey (DES) Science Verification (SV) data. Our lens sample consists of red galaxies, known as redMaGiC, which are specifically selected to have a low photometric redshift error and outlier rate. The lensing measurement has a total signal-to-noise ratio of 29 over scales 0.09 < R < 15 Mpc h(-1), including all lenses over a wide redshift range 0.2 < z < 0.8. Dividing the lenses into three redshift bins for this constant moving number density sample, we find no evidence for evolution in the halo mass with redshift. We obtain consistent results for the lensing measurement with two independent shear pipelines, NGMIX and IM3SHAPE. We perform a number of null tests on the shear and photometric redshift catalogues and quantify resulting systematic uncertainties. Covariances from jackknife subsamples of the data are validated with a suite of 50 mock surveys. The result and systematic checks in this work provide a critical input for future cosmological and galaxy evolution studies with the DES data and redMaGiC galaxy samples. We fit a halo occupation distribution (HOD) model, and demonstrate that our data constrain the mean halo mass of the lens galaxies, despite strong degeneracies between individual HOD parameters.

Galaxy bias from galaxy-galaxy lensing in the DES Science Verification Data

We present a measurement of galaxy–galaxy lensing around a magnitude-limited (iAB < 22.5) sample of galaxies from the dark energy survey science verification (DES-SV) data. We split these lenses into three photometric-redshift bins from 0.2 to 0.8, and determine the product of the galaxy bias b and cross-correlation coefficient between the galaxy and dark matter overdensity fields r in each bin, using scales above 4 h−1 Mpc comoving, where we find the linear bias model to be valid given our current uncertainties. We compare our galaxy bias results from galaxy–galaxy lensing with those obtained from galaxy clustering and CMB lensing for the same sample of galaxies, and find our measurements to be in good agreement with those in Crocce et al., while, in the lowest redshift bin (z ∼ 0.3), they show some tension with the findings in Giannantonio et al. We measure b· r to be 0.87 ± 0.11, 1.12 ± 0.16 and 1.24 ± 0.23, respectively, for the three redshift bins of width Δz = 0.2 in the range 0.2 < z < 0.8, defined with the photometric-redshift algorithm BPZ. Using a different code to split the lens sample, TPZ, leads to changes in the measured biases at the 10–20 per cent level, but it does not alter the main conclusion of this work: when comparing with Crocce et al. we do not find strong evidence for a cross-correlation parameter significantly below one in this galaxy sample, except possibly at the lowest redshift bin (z ∼ 0.3), where we find r = 0.71 ± 0.11 when using TPZ, and 0.83 ± 0.12 with BPZ.

DES Y1 Results: validating cosmological parameter estimation using simulated Dark Energy Surveys

We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey data, they provide powerful validation tests of the DES Y1 cosmological analyses presented in companion papers. We use two suites of galaxy simulations produced using different methods, which therefore provide independent tests of our cosmological parameter inference. The cosmological analysis we aim to validate is presented in DES Collaboration et al. (2017) and uses angular two-point correlation functions of galaxy number counts and weak lensing shear, as well as their cross-correlation, in multiple redshift bins. While our constraints depend on the specific set of simulated realisations available, for both suites of simulations we find that the input cosmology is consistent with the combined constraints from multiple simulated DES Y1 realizations in the Omega(m) - sigma(8) plane. For one of the suites, we are able to show with high confidence that any biases in the inferred S-8 = sigma(8)(Omega(m)/0.3)(0.5) and Omega(m) are smaller than the DES Y1 1 - sigma uncertainties. For the other suite, for which we have fewer realizations, we are unable to be this conclusive;we infer a roughly 60 per cent (70 per cent) probability that systematic bias in the recovered Omega(m) (S-8) is sub-dominant to the DES Y1 uncertainty. As cosmological analyses of this kind become increasingly more precise, validation of parameter inference using survey simulations will be essential to demonstrate robustness.

The Splashback Feature around DES Galaxy Clusters: Galaxy Density and Weak Lensing Profiles

Splashback refers to the process of matter that is accreting onto a dark matter halo reaching its first orbital apocenter and turning around in its orbit. The clustercentric radius at which this process occurs, r(sp), defines a halo boundary that is connected to the dynamics of the cluster. A rapid decline in the halo profile is expected near rsp. We measure the galaxy number density and weak lensing mass profiles around REDMAPPER galaxy clusters in the first-year Dark Energy Survey (DES) data. For a cluster sample with mean M-200m mass approximate to 2.5 x 10(14)M(circle dot), we find strong evidence of a splashback-like steepening of the galaxy density profile and measure r(sp) = 1.13 +/- 0.07 h(-1) Mpc, consistent with the earlier Sloan Digital Sky Survey measurements of More et al. and Baxter et al. Moreover, our weak lensing measurement demonstrates for the first time the existence of a splashback-like steepening of the matter profile of galaxy clusters. We measure r(sp) = 1.34 +/- 0.21 h(-1) Mpc from the weak lensing data, in good agreement with our galaxy density measurements. For different cluster and galaxy samples, we find that, consistent with.CDM simulations, rsp scales with R-200m and does not evolve with redshift over the redshift range of 0.3-0.6. We also find that potential systematic effects associated with the REDMAPPER algorithm may impact the location of rsp. We discuss the progress needed to understand the systematic uncertainties and fully exploit forthcoming data from DES and future surveys, emphasizing the importance of more realistic mock catalogs and independent cluster samples.