LoCuSS: The Mass Density Profile of Massive Galaxy Clusters at z=0.2

TL;DR

This study uses stacked weak-lensing analysis of 50 galaxy clusters at z=0.2 to precisely measure their mass density profile, confirming theoretical predictions and demonstrating the method's potential for future large surveys.

Contribution

Developed a new background galaxy selection method and applied stacked weak-lensing to accurately determine cluster mass and concentration at z=0.2.

Findings

Detected strong shear signal with S/N=32.7

Measured mass Mvir≈7.19×10^{14}h^{-1}M⊙ and concentration cvir≈5.41

Results align with theoretical models and show low systematic errors.

Abstract

We present a stacked weak-lensing analysis of an approximately mass-selected sample of 50 galaxy clusters at 0.15<z<0.3, based on observations with Suprime-Cam on the Subaru Telescope. We develop a new method for selecting lensed background galaxies from which we estimate that our sample of red background galaxies suffers just 1% contamination. We detect the stacked tangential shear signal from the full sample of 50 clusters, based on this red sample of background galaxies, at a total signal-to-noise ratio of S/N=32.7. The Navarro-Frenk-White model is an excellent fit to the data, yielding sub-10% statistical precision on mass and concentration: Mvir=7.19^{+0.53}_{-0.50}\times10^{14}h^{-1}Msol, cvir=5.41^{+0.49}_{-0.45} (c_{200}=4.22^{+0.40}_{-0.36}). Tests of a range of possible systematic errors, including shear calibration and stacking-related issues, indicate that they are sub-dominant to the statistical errors. The concentration parameter obtained from stacking our approximately mass-selected cluster sample is broadly in line with theoretical predictions. Moreover, the uncertainty on our measurement is comparable with the differences between the different predictions in the literature. Overall our results highlight the potential for stacked weak-lensing methods to probe the mean mass density profile of cluster-scale dark matter halos with upcoming surveys, including Hyper-Suprime-Cam, Dark Energy Survey, and KIDS.