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Register a new userVelocity Dispersions of Clusters in the Dark Energy Survey Y3 redMaPPer Catalog
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We measure the velocity dispersions of clusters of galaxies selected by the redMaPPer algorithm in the first three years of data from the Dark Energy Survey (DES), allowing us to probe cluster selection and richness estimation, $lambda$, in light of cluster dynamics. Our sample consists of 126 clusters with sufficient spectroscopy for individual velocity dispersion estimates. We examine the correlations between cluster velocity dispersion, richness, X-ray temperature and luminosity as well as central galaxy velocity offsets. The velocity dispersion-richness relation exhibits a bimodal distribution. The majority of clusters follow scaling relations between velocity dispersion, richness, and X-ray properties similar to those found for previous samples; however, there is a significant population of clusters with velocity dispersions which are high for their richness. These clusters account for roughly 20% of the $lambda < 70$ systems in our sample, but more than half of $lambda < 70$ clusters at $z>0.5$. A couple of these systems are hot and X-ray bright as expected for massive clusters with richnesses that appear to have been underestimated, but most appear to have high velocity dispersions for their X-ray properties likely due to line-of-sight structure. These results suggest that projection effects contribute significantly to redMaPPer selection, particularly at higher redshifts and lower richnesses. The redMaPPer determined richnesses for the velocity dispersion outliers are consistent with their X-ray properties, but several are X-ray undetected and deeper data is needed to understand their nature.
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We use weak-lensing shear measurements to determine the mean mass of optically selected galaxy clusters in Dark Energy Survey Science Verification data. In a blinded analysis, we split the sample of more than 8,000 redMaPPer clusters into 15 subsets, spanning ranges in the richness parameter $5 leq lambda leq 180$ and redshift $0.2 leq z leq 0.8$, and fit the averaged mass density contrast profiles with a model that accounts for seven distinct sources of systematic uncertainty: shear measurement and photometric redshift errors; cluster-member contamination; miscentering; deviations from the NFW halo profile; halo triaxiality; and line-of-sight projections. We combine the inferred cluster masses to estimate the joint scaling relation between mass, richness and redshift, $mathcal{M}(lambda,z) varpropto M_0 lambda^{F} (1+z)^{G}$. We find $M_0 equiv langle M_{200mathrm{m}},|,lambda=30,z=0.5rangle=left[ 2.35 pm 0.22 rm{(stat)} pm 0.12 rm{(sys)} right] cdot 10^{14} M_odot$, with $F = 1.12,pm,0.20 rm{(stat)}, pm, 0.06 rm{(sys)}$ and $G = 0.18,pm, 0.75 rm{(stat)}, pm, 0.24 rm{(sys)}$. The amplitude of the mass-richness relation is in excellent agreement with the weak-lensing calibration of redMaPPer clusters in SDSS by Simet et al. (2016) and with the Saro et al. (2015) calibration based on abundance matching of SPT-detected clusters. Our results extend the redshift range over which the mass-richness relation of redMaPPer clusters has been calibrated with weak lensing from $zleq 0.3$ to $zleq0.8$. Calibration uncertainties of shear measurements and photometric redshift estimates dominate our systematic error budget and require substantial improvements for forthcoming studies.
We constrain the mass--richness scaling relation of redMaPPer galaxy clusters identified in the Dark Energy Survey Year 1 data using weak gravitational lensing. We split clusters into $4times3$ bins of richness $lambda$ and redshift $z$ for $lambdageq20$ and $0.2 leq z leq 0.65$ and measure the mean masses of these bins using their stacked weak lensing signal. By modeling the scaling relation as $langle M_{rm 200m}|lambda,zrangle = M_0 (lambda/40)^F ((1+z)/1.35)^G$, we constrain the normalization of the scaling relation at the 5.0 per cent level as $M_0 = [3.081 pm 0.075 ({rm stat}) pm 0.133 ({rm sys})] cdot 10^{14} {rm M}_odot$ at $lambda=40$ and $z=0.35$. The richness scaling index is constrained to be $F=1.356 pm 0.051 ({rm stat})pm 0.008 ({rm sys})$ and the redshift scaling index $G=-0.30pm 0.30 ({rm stat})pm 0.06 ({rm sys})$. These are the tightest measurements of the normalization and richness scaling index made to date. We use a semi-analytic covariance matrix to characterize the statistical errors in the recovered weak lensing profiles. Our analysis accounts for the following sources of systematic error: shear and photometric redshift errors, cluster miscentering, cluster member dilution of the source sample, systematic uncertainties in the modeling of the halo--mass correlation function, halo triaxiality, and projection effects. We discuss prospects for reducing this systematic error budget, which dominates the uncertainty on $M_0$. Our result is in excellent agreement with, but has significantly smaller uncertainties than, previous measurements in the literature, and augurs well for the power of the DES cluster survey as a tool for precision cosmology and upcoming galaxy surveys such as LSST, Euclid and WFIRST.
We introduce a galaxy cluster mass observable, $mu_star$, based on the stellar masses of cluster members, and we present results for the Dark Energy Survey (DES) Year 1 observations. Stellar masses are computed using a Bayesian Model Averaging method, and are validated for DES data using simulations and COSMOS data. We show that $mu_star$ works as a promising mass proxy by comparing our predictions to X-ray measurements. We measure the X-ray temperature-$mu_star$ relation for a total of 150 clusters matched between the wide-field DES Year 1 redMaPPer catalogue, and Chandra and XMM archival observations, spanning the redshift range $0.1<z<0.7$. For a scaling relation which is linear in logarithmic space, we find a slope of $alpha = 0.488pm0.043$ and a scatter in the X-ray temperature at fixed $mu_star$ of $sigma_{{rm ln} T_X|mu_star}=0.266^{+0.019}_{-0.020}$ for the joint sample. By using the halo mass scaling relations of the X-ray temperature from the Weighing the Giants program, we further derive the $mu_star$-conditioned scatter in mass, finding $sigma_{{rm ln} M|mu_star}=0.26^{+ 0.15}_{- 0.10}$. These results are competitive with well-established cluster mass proxies used for cosmological analyses, showing that $mu_star$ can be used as a reliable and physically motivated mass proxy to derive cosmological constraints.
We present optical spectroscopy of galaxies in clusters detected through the Sunyaev-Zeldovich (SZ) effect with the South Pole Telescope (SPT). We report our own measurements of $61$ spectroscopic cluster redshifts, and $48$ velocity dispersions each calculated with more than $15$ member galaxies. This catalog also includes $19$ dispersions of SPT-observed clusters previously reported in the literature. The majority of the clusters in this paper are SPT-discovered; of these, most have been previously reported in other SPT cluster catalogs, and five are reported here as SPT discoveries for the first time. By performing a resampling analysis of galaxy velocities, we find that unbiased velocity dispersions can be obtained from a relatively small number of member galaxies ($lesssim 30$), but with increased systematic scatter. We use this analysis to determine statistical confidence intervals that include the effect of membership selection. We fit scaling relations between the observed cluster velocity dispersions and mass estimates from SZ and X-ray observables. In both cases, the results are consistent with the scaling relation between velocity dispersion and mass expected from dark-matter simulations. We measure a $sim$30% log-normal scatter in dispersion at fixed mass, and a $sim$10% offset in the normalization of the dispersion-mass relation when compared to the expectation from simulations, which is within the expected level of systematic uncertainty.
We present the weak lensing mass calibration of the stellar mass based $mu_{star}$ mass proxy for redMaPPer galaxy clusters in the Dark Energy Survey Year 1. For the first time we are able to perform a calibration of $mu_{star}$ at high redshifts, $z>0.33$. In a blinded analysis, we use $sim 6,000$ clusters split into 12 subsets spanning the ranges $0.1 leqslant z<0.65$ and $mu_{star}$ up to $sim 5.5 times 10^{13} M_{odot}$, and infer the average masses of these subsets through modelling of their stacked weak lensing signal. In our model we account for the following sources of systematic uncertainty: shear measurement and photometric redshift errors, miscentring, cluster-member contamination of the source sample, deviations from the NFW halo profile, halo triaxiality and projection effects. We use the inferred masses to estimate the joint mass--$mu_{star}$--$z$ scaling relation given by $langle M_{200c} | mu_{star},z rangle = M_0 (mu_{star}/5.16times 10^{12} mathrm{M_{odot}})^{F_{mu_{star}}} ((1+z)/1.35)^{G_z}$. We find $M_0= (1.14 pm 0.07) times 10^{14} mathrm{M_{odot}}$ with $F_{mu_{star}}= 0.76 pm 0.06$ and $G_z= -1.14 pm 0.37$. We discuss the use of $mu_{star}$ as a complementary mass proxy to the well-studied richness $lambda$ for: $i)$ exploring the regimes of low $z$, $lambda<20$ and high $lambda$, $z sim 1$; $ii)$ testing systematics such as projection effects for applications in cluster cosmology.
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