2017A&A...598A..61B

Massive, high-redshift, galaxy clusters are useful laboratories to test cosmological models and to probe structure formation and evolution, but observations are challenging due to cosmological dimming and angular distance effects. Here we present a pilot X-ray study of the five most massive (M₅₀₀>5x10¹⁴M_☉), distant (z∼1), clusters detected via the Sunyaev-Zel'Dovich effect. We optimally combine XMM-Newton and Chandra X-ray observations by leveraging the throughput of XMM-Newton to obtain spatially-resolved spectroscopy, and the spatial resolution of Chandra to probe the bright inner parts and to detect embedded point sources. Capitalising on the excellent agreement in flux-related measurements, we present a new method to derive the density profiles, which are constrained in the centre by Chandra and in the outskirts by XMM-Newton. We show that the Chandra-XMM-Newton combination is fundamental for morphological analysis at these redshifts, the Chandra resolution being required to remove point source contamination, and the XMM-Newton sensitivity allowing higher significance detection of faint substructures. Measuring the morphology using images from both instruments, we found that the sample is dominated by dynamically disturbed objects. We use the combined Chandra-XMM-Newton density profiles and spatially-resolved temperature profiles to investigate thermodynamic quantities including entropy and pressure. From comparison of the scaled profiles with the local REXCESS sample, we find no significant departure from standard self-similar evolution, within the dispersion, at any radius, except for the entropy beyond 0.7R₅₀₀. The baryon mass fraction tends towards the cosmic value, with a weaker dependence on mass than that observed in the local Universe. We make a comparison with the predictions from numerical simulations. The present pilot study demonstrates the utility and feasibility of spatially-resolved analysis of individual objects at high-redshift through the combination of XMM-Newton and Chandra observations. Observations of a larger sample will allow a fuller statistical analysis to be undertaken, in particular of the intrinsic scatter in the structural and scaling properties of the cluster population.