Exploring the hydrostatic mass bias in MUSIC clusters: application to the NIKA2 mock sample

TL;DR

This study analyzes hydrostatic mass bias in galaxy clusters using synthetic data from the MUSIC simulation, revealing a bias around 20% influenced by non-thermal pressure and cluster dynamical state, with implications for cosmological measurements.

Contribution

It provides a detailed assessment of hydrostatic mass bias in simulated clusters and explores the impact of non-thermal pressure and cluster relaxation on mass estimates.

Findings

Hydrostatic mass bias is approximately 20%.

Using temperature yields smaller bias than pressure.

Non-thermal motions account for the bias.

Abstract

Clusters of galaxies are useful tools to constrain cosmological parameters, only if their masses can be correctly inferred from observations. In particular, X-ray and Sunyaev-Zeldovich (SZ) effect observations can be used to derive masses within the framework of the hydrostatic equilibrium. Therefore, it is crucial to have a good control of the possible mass biases that can be introduced when this hypothesis is not valid. In this work, we analyzed a set of 260 synthetic clusters from the MUSIC simulation project, at redshifts $0 \leq z \leq 0.82$. We estimate the hydrostatic mass of the MUSIC clusters from X-ray only (temperature and density) and from X-ray and SZ (density and pressure). Then, we compare them with the true 3D dynamical mass. The biases are of the order of 20%. We find that using the temperature instead of the pressure leads to a smaller bias, although the two values are compatible within 1$\sigma$. Non-thermal contributions to the total pressure support, arising from bulk motion and turbulence of the gas, are also computed and show that they are sufficient to account for this bias. We also present a study of the correlation between the mass bias and the dynamical state of the clusters. A clear correlation is shown between the relaxation state of the clusters and the bias factor. We applied the same analysis on a subsample of 32 objects, already selected for supporting the NIKA2 SZ Large Program.