On the interpretation of XRISM X-ray measurements of turbulence in the intracluster medium: a comparison with cosmological simulations

TL;DR

This study compares XRISM X-ray measurements of turbulence in the Coma galaxy cluster with high-resolution cosmological simulations, finding that realistic, patchy turbulence models align well with observations and challenge previous assumptions of steeper turbulence spectra.

Contribution

It demonstrates that cosmological simulations with patchy, Kolmogorov-like turbulence spectra can explain XRISM observations, resolving previous tensions and emphasizing the importance of combining data with advanced simulations.

Findings

Simulation results are compatible with XRISM measurements.

Turbulence in galaxy clusters is patchy and spectrum aligns with Kolmogorov.

Steeper turbulence spectra are not necessary to explain observations.

Abstract

We investigate whether the properties of turbulent gas motions recently measured via X-ray spectroscopy in the Coma cluster of galaxies by XRISM are in tension with the turbulent picture established by current numerical cosmological simulations. We use a high-resolution simulation of a Coma-like cluster and show that the simulation yields velocity structure functions and X-ray line-widths that are compatible with those measured by the XRISM observations of Coma. In particular, it has been previously suggested that a much steeper turbulence spectrum than the Kolmogorov would be needed to explain the XRISM observations under a homogeneous, cluster volume-filling turbulence model. Our results show that this tension is overcome thanks to the more complicated turbulent picture in cosmological simulations, that indeed shows a patchy distribution of turbulent regions in galaxy clusters, with a spectrum that is generally consistent with a Kolmogorov power-law over a fairly wide range of scales. More generally, our study highlights the fact that the interpretation of XRISM data of galaxy clusters depends on the turbulence model used and the importance of combining data and advanced simulations in the future steps.