Investigating the turbulent hot gas in X-COP galaxy clusters

Abstract

Context. Turbulent processes at work in the intracluster medium perturb this environments, impacting its properties, displacing gas, and creating local density fluctuations that can be quantified via X-ray surface brightness fluctuation analyses. Improved knowledge of these phenomena would allow for a more accurate determination of the mass of galaxy clusters, as well as a better understanding of their dynamic assembly. Aims. In this work, we aim to set constraints on the structure of turbulence using X-ray surface brightness fluctuations. We seek to consider the stochastic nature of this observable and to constrain the structure of the underlying power spectrum. Methods. We propose a new Bayesian approach, relying on simulation-based inference to account for the whole error budget. We used the X-COP cluster sample to individually constrain the power spectrum in four regions and within R500. We spread the analysis on the entire set of 12 systems to alleviate the sample variance. We then interpreted the density fluctuations as the result of either gas clumping or turbulence. Results. For each cluster considered individually, the normalisation of density fluctuations correlate positively with the Zernike moment and centroid shift, but negatively with the concentration and the Gini coefficient. The spectral index within R500 and evaluated over all clusters is consistent with a Kolmogorov cascade. The normalisation of density fluctuations, when interpreted in terms of clumping, is consistent within 0.5R500 with the literature results and numerical simulations; however, it is higher between 0.5 and 1R500. Conversely, when interpreted on the basis of turbulence, we deduce a non-thermal pressure profile that is lower than the predictions of the simulations within 0.5 R500, but still in agreement in the outer regions. We explain these results by the presence of central structural residues that are remnants of the dynamical assembly of the clusters.

Surface Brightness Fluctuations in Two SPT Clusters: A Pilot Study

“…The amplitude of fluctuations we recover in these two clusters is larger than those seen in several other studies (e.g., Churazov et al 2012;Gaspari & Churazov 2013;Zhuravleva et al 2015;Arévalo et al 2016;Hofmann et al 2016;Eckert et al 2017;Hernández-Lang et al 2023), but in line with other studies which probe similar physical scales (e.g., Khatri & Gaspari 2016;Dupourqué et al 2023). We estimate the Mach number for each ring based on three methods (scaling relations): (1) relating the peak of the amplitude spectrum to the Mach number, (2) relating the integrated power spectrum to the Mach number, and (3) combining the two previous methods by taking the average of their respectively derived Mach numbers.…”

“…It is hopefully evident that when considering elliptical models, the parameter space is immediately inflated: geometrically one must choose which ellipticity is appropriate and what to assume about the third ellipsoidal axis and inclination. Similar to previous discussions (e.g., Zhuravleva et al 2015;Romero et al 2023), it is unclear what would be correct, though some choice is taken in Dupourqué et al (2023) and Zhang et al (2023), where we note Zhang et al (2023) models a circular β-model for the core and uses an elliptical β-model for the broader emission. There are further considerations in terms of deprojection, and deriving a hydrostatic mass bias for an ellipsoidal potential and how to define R 500 in this framework.…”