JoXSZ: Joint X-SZ fitter for galaxy clusters

TL;DR

JoXSZ is a Bayesian Python tool that jointly fits SZ and X-ray data to derive comprehensive thermodynamic profiles of galaxy clusters, enhancing the analysis of intracluster medium properties.

Contribution

It introduces a novel joint fitting method that combines SZ and X-ray data for the first time, enabling detailed thermodynamic profiling of galaxy clusters.

Findings

First joint SZ and X-ray thermodynamic profiles derived

Enhanced accuracy in intracluster medium characterization

Open-source implementation available on GitHub

Abstract

High-resolution observations of the thermal Sunyaev-Zeldovich (SZ) effect and of the X-ray emission of galaxy clusters are becoming more and more widespread, offering us an unique asset to the study of the thermodynamic properties of the intracluster medium. We present JoXSZ, a Bayesian forward-modelling Python code designed to jointly fit the SZ data and the three dimensional X-ray data cube. JoXSZ is able to derive the thermodynamic profiles of galaxy clusters for the first time making full and consistent use of all the information contained in the observations. JoXSZ will be publicly available on GitHub in the near future.