The "Cluster HEritage project with XMM-Newton: Mass Assembly and Thermodynamics at the End point of structure formation" (CHEX-MATE) is a multi-year heritage program to obtain homogeneous XMM-Newton observations of a representative sample of 118 galaxy clusters. The observations are tuned to reconstruct the distribution of the main thermodynamic quantities of the intra-cluster medium up to R500 and to obtain individual mass measurements, via the hydrostatic-equilibrium equation, with a precision of 15−20%. Temperature profiles are a necessary ingredient for the scientific goals of the project and it is thus crucial to derive the best possible temperature measurements from our data. This is why we have built a new pipeline for spectral extraction and analysis of XMM-Newton data, based on a new physically motivated background model and on a Bayesian approach with Markov chain Monte Carlo methods, which we present in this paper for the first time. We applied this new method to a subset of 30 galaxy clusters representative of the CHEX-MATE sample and show that we can obtain reliable temperature measurements up to regions where the source intensity is as low as 20% of the background, keeping systematic errors below 10%. We compare the median profile of our sample and the best-fit slope at large radii with literature results and we find a good agreement with other measurements based on XMM-Newton data. Conversely, when we exclude the most contaminated regions, where the source intensity is below 20% of the background, we find significantly flatter profiles, in agreement with predictions from numerical simulations and independent measurements with a combination of Sunyaev-Zeldovich and X-ray imaging data.
