Physical modelling of galaxy clusters using Einasto dark matter profiles

TL;DR

This paper compares two physical models of galaxy clusters using Sunyaev--Zel'dovich data, one with an NFW dark matter profile and the other with an Einasto profile, to evaluate their effectiveness in mass estimation.

Contribution

It introduces an Einasto profile-based model for galaxy clusters and compares its performance to the traditional NFW profile model using simulations and real data.

Findings

Bayesian evidence shows no strong preference for either model in most simulations.

Mass estimates are more accurate when using the correct model, within 1σ of input values.

Models produce consistent mass estimates for real data except under extreme parameter choices.

Abstract

We derive a model for Sunyaev--Zel'dovich data from a galaxy cluster which uses an Einasto profile to model the cluster's dark matter component. This model is similar to the physical models for clusters previously used by the Arcminute Microkelvin Imager (AMI) consortium, which model the dark matter using a Navarro-Frenk-White (NFW) profile, but the Einasto profile provides an extra degree of freedom. We thus present a comparison between two physical models which differ only in the way they model dark matter: one which uses an NFW profile (PM I) and one that uses an Einasto profile (PM II). We illustrate the differences between the models by plotting physical properties of clusters as a function of cluster radius. We generate AMI simulations of clusters which are \textit{created} and \textit{analysed} with both models. From this we find that for 14 of the 16 simulations, the Bayesian evidence gives no preference to either of the models according to the Jeffreys scale, and for the other two simulations, weak preference in favour of the correct model. However, for the mass estimates obtained from the analyses, the values were within $1\sigma$ of the input values for 14 out of 16 of the clusters when using the correct model, but only in 6 out of 16 cases when the incorrect model was used to analyse the data. Finally we apply the models to real data from cluster A611 obtained with AMI, and find the mass estimates to be consistent with one another except in the case of when PM II is applied using an extreme value for the Einasto shape parameter.