Assessing the impact of modelling assumptions on Sunyaev-Zel’dovich effect surface brightness fluctuations power spectra

Galaxy clusters are important objects of study for cosmology. In particular, it would be very useful for cosmological models to find a way to precisely and accurately measure their mass. The mass of the galaxy cluster can be estimated by using the thermodynamic properties of the plasma and assuming hydrostatic equilibrium. However, there is a bias in this mass estimate that might be caused by turbulence in the intra-cluster medium. Turbulence can be studied using surface brightness fluctuations, captured using either X-ray methods or observations of the Sunyaev-Zel’dovich effect. In order to extract fluctuations from the cluster’s general or global characteristics, they must be modelled. As such, extracting surface brightness fluctuations implicitly carries with it a set of assumptions about the smooth model of the galaxy cluster.

This thesis will focus on observations of the Sunyaev-Zel’dovich effect and will investigate several candidate procedures for generating a smooth model, and the effect that each method has on the resultant surface brightness fluctuations, power spectrum, and pressure power spectrum. Using radial averaging, Gaussian averaging, and multiple wavelet-based methods, I analyse the surface brightness fluctuations in the Coma cluster and compare power spectra generated by these different methods to published estimates. I conclude that the assumptions that go into the smooth model have a significant effect on the surface brightness fluctuations and identify wavelet-based methods as a promising way of separating global behaviour from local with a minimal set of assumptions.