Evolution of X-ray galaxy cluster properties in a representative sample (EXCPReS)

Optimal binning for temperature profile extraction

¹ Université Paris-Saclay, Université Paris Cité, CEA, CNRS, AIM, 91191 Gif-sur-Yvette, France
e-mail: gabriel.pratt@cea.fr
² IRAP, CNRS, Université de Toulouse, CNES, UT3-UPS, Toulouse, France

Received: 27 October 2023
Accepted: 26 April 2024

Abstract

We present XMM-Newton observations of a representative X-ray selected sample of 31 galaxy clusters at moderate redshift (0.4 < z < 0.6), spanning the mass range 10¹⁴ < M₅₀₀ < 10¹⁵ M_⊙. This sample, EXCPReS (Evolution of X-ray galaxy Cluster Properties in a Representative Sample), is used to test and validate a new method to produce optimally-binned cluster X-ray temperature profiles. The method uses a dynamic programming algorithm, based on partitioning of the soft-band X-ray surface brightness profile, to obtain a binning scheme that optimally fulfils a given signal-to-noise threshold criterion out to large radius. From the resulting optimally-binned EXCPReS temperature profiles, and combining with those from the local REXCESS sample, we provide a generic scaling relation between the relative error on the temperature and the [0.3–2] keV surface brightness signal-to-noise ratio, and its dependence on temperature and redshift. We derive an average scaled 3D temperature profile for the sample. Comparing to the average scaled 3D temperature profiles from REXCESS, we find no evidence for evolution of the average profile shape within the redshift range that we probe.