http://arxiv.org/abs/1809.03325
We derive a model for Sunyaev–Zel’dovich data of galaxy clusters which uses an Einasto profile to model their dark matter component. This model is similar to the physical models for clusters previously used by the 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 apply the models to real data from cluster A611 obtained with the Arcminute Microkelvin Imager (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. Finally we generate AMI simulations of clusters which are \textit{created} and \textit{analysed} with both models. From this we find that for 15 of the 16 simulations, PM II recovers the input masses more accurately than PM I. The Bayesian evidence values calculated from these analyses suggest that PM II provides a better fit to the data than PM I for 13 of the clusters, but the preference is statistically significant for only three of these according to the Jeffreys scale.
K. Javid, Y. Perrott, C. Rumsey, et. al.
Tue, 11 Sep 18
2/62
Comments: 14 pages, 9 figures, 3 tables, 28 equations, MNRAS 2018, under review