Mass modelling of Abell 2634: avoiding the interloper bias

TL;DR

This paper examines how interloper contamination affects mass modeling of galaxy clusters, using Abell 2634 as a case study, and compares methods for removing interlopers to improve accuracy.

Contribution

It evaluates multiple interloper removal techniques and identifies the most reliable methods for accurate mass modeling of galaxy clusters.

Findings

Two interloper removal methods yield consistent galaxy samples.

Reliable NFW profile parameters are obtained after effective interloper removal.

Interloper contamination significantly biases mass estimates if not properly addressed.

Abstract

Using an example of the Abell 2634 galaxy cluster we discuss the effect of contamination of kinematic data by interlopers and its impact on mass modelling. The cluster data reveal rich substructure along the line of sight. We demonstrate that it is necessary to apply a few independent methods of interloper removal in order to obtain a reliable sample of cluster members. We present results of three such methods which are commonly used in the literature and have been recently extensively tested on simulated data. Only two of them lead to consistent and reliable samples of cluster galaxies. For both of them we provide parameters of the best-fitting NFW density profile by fitting an isotropic solution of the Jeans equation to the velocity dispersion profiles.