Monthly Notices of the Royal Astronomical Society · 2014 · 269 citations · 88 references
Natural SciencesAstronomyPhysicsAstrophysicsCosmologyObservational AstronomyGalaxy ClustersGravitational LensingObservational CosmologyRed GiantsStar ClustersCatalog BiasesCluster CosmologyCluster LensingCluster Mass EstimationPhotometrySurvey PhotometrySystematic Uncertainty AnalysisWeak Gravitational Lensing Of Clusters
We report weak-lensing masses for 51 of the most X-ray luminous galaxy clusters known. This cluster sample, introduced earlier in this series of papers, spans redshifts 0.15 < z_cl < 0.7, and is well suited to calibrate mass proxies for current cluster cosmology experiments. Cluster masses are measured with a standard `color-cut' lensing method from three-filter photometry of each field. Additionally, for 27 cluster fields with at least five-filter photometry, we measure high-accuracy masses using a new method that exploits all information available in the photometric redshift posterior probability distributions of individual galaxies. Using simulations based on the COSMOS-30 catalog, we demonstrate control of systematic biases in the mean mass of the sample with this method, from photometric redshift biases and associated uncertainties, to better than 3%. In contrast, we show that the use of single-point estimators in place of the full photometric redshift posterior distributions can lead to significant redshift-dependent biases on cluster masses. The performance of our new photometric redshift-based method allows us to calibrate `color-cut` masses for all 51 clusters in the present sample to a total systematic uncertainty of ~7% on the mean mass, a level sufficient to significantly improve current cosmology constraints from galaxy clusters. Our results bode well for future cosmological studies of clusters, potentially reducing the need for exhaustive spectroscopic calibration surveys as compared to other techniques, when deep, multi-filter optical and near-IR imaging surveys are coupled with robust photometric redshift methods.
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