Galaxy Cluster Mass Estimates in the Presence of Substructure

TL;DR

This paper introduces a new model for analyzing galaxy cluster kinematics that accounts for substructures and contamination, leading to more accurate mass estimates and insights into cluster dynamics.

Contribution

The paper develops a comprehensive model that incorporates substructure, contamination, and rotation in galaxy clusters, improving mass estimation accuracy.

Findings

Substructure reduces the estimated cluster mass by ~20%.

Identified up to five galaxy subpopulations within A267.

Cluster mass and concentration are consistent with cosmological simulations.

Abstract

We develop and implement a model to analyze the internal kinematics of galaxy clusters that may contain subpopulations of galaxies that do not independently trace the cluster potential. The model allows for substructures within the cluster environment, disentangles cluster members from contaminating foreground and background galaxies, and includes an overall cluster rotation term as part of the cluster kinematics. We estimate the cluster velocity dispersion and/or mass while marginalizing over uncertainties in all of the above complexities. In a first application to our published data for Abell 267 (A267), we find no evidence for cluster rotation but we identify up to five distinct galaxy subpopulations. We use these results to explore the sensitivity of inferred cluster properties to the treatment of substructure. Compared to a model that assumes no substructure, our substructure model reduces the dynamical mass of A267 by $\sim 20\%$ and shifts the cluster mean velocity by $\sim 100$ km s$^{-1}$, approximately doubling the offset with respect to the velocity of A267's brightest cluster galaxy. Embedding the spherical Jeans equation within this framework, we infer for A267 a dark matter halo of mass $M_{200}=6.77\pm1.06\times10^{14}M_\odot/h$, concentration $\log_{10}c_{200}=0.61\pm0.39$, consistent with the mass-concentration relation found in cosmological simulations.