Precise Mass Determination of SPT-CL J2106-5844, the Most Massive Cluster at z>1

TL;DR

This study uses high-resolution weak-lensing data from Hubble to precisely measure the mass of the most massive known galaxy cluster at redshift greater than 1, revealing a complex, possibly merging structure.

Contribution

It provides the first detailed weak-lensing analysis of SPT-CL J2106-5844, confirming its status as the most massive z>1 cluster and revealing its complex mass distribution.

Findings

Cluster mass estimated at ~10.4 x 10^14 solar masses.

Mass distribution is asymmetric with multiple substructures.

Cluster likely undergoing a merger process.

Abstract

We present a detailed high-resolution weak-lensing (WL) study of SPT-CL J2106-5844 at z=1.132, claimed to be the most massive system discovered at z > 1 in the South Pole Telescope Sunyaev-Zel'dovich (SPT-SZ) survey. Based on the deep imaging data from the Advanced Camera for Surveys and Wide Field Camera 3 on-board the Hubble Space Telescope, we find that the cluster mass distribution is asymmetric, composed of a main clump and a subclump ~640 kpc west thereof. The central clump is further resolved into two smaller northwestern and southeastern substructures separated by ~150 kpc. We show that this rather complex mass distribution is more consistent with the cluster galaxy distribution than a unimodal distribution as previously presented. The northwestern substructure coincides with the BCG and X-ray peak while the southeastern one agrees with the location of the number density peak. These morphological features and the comparison with the X-ray emission suggest that the cluster might be a merging system. We estimate the virial mass of the cluster to be $M_{200c} = (10.4^{+3.3}_{-3.0}\pm1.0)~\times~10^{14}~M_{\odot}$, where the second error bar is the systematic uncertainty. Our result confirms that the cluster SPT-CL J2106-5844 is indeed the most massive cluster at z>1 known to date. We demonstrate the robustness of this mass estimate by performing a number of tests with different assumptions on the centroids, mass-concentration relations, and sample variance.