The Cluster HEritage project with XMM-Newton: Mass Assembly and Thermodynamics at the Endpoint of structure formation. I. Programme overview

Creators: Arnaud, M.; Ettori, S.; Pratt, G. W.; Rossetti, M.; Eckert, D.; Gastaldello, F.; Gavazzi, R.; Kay, S. T.; Lovisari, L.; Maughan, B. J.; Pointecouteau, E.; Sereno, M.; Bartalucci, I.; Bonafede, A.; Bourdin, H.; Cassano, R.; Duffy, R. T.; Iqbal, A.; Maurogordato, S.; Rasia, E.; Sayers, J.; Andrade-Santos, F.; Aussel, H.; Barnes, D. J.; Barrena, R.; Borgani, S.; Burkutean, S.; Clerc, N.; Corasaniti, P.-S.; Cuillandre, J.-C.; De Grandi, S.; De Petris, M.; Dolag, K.; Donahue, M.; Ferragamo, A.; Gaspari, M.; Ghizzardi, S.; Gitti, M.; Haines, C. P.; Jauzac, M.; Johnston-Hollitt, M.; Jones, C.; Kéruzoré, F.; LeBrun, A. M. C.; Mayet, F.; Mazzotta, P.; Melin, J.-B.; Molendi, S.; Nonino, M.; Okabe, N.; Paltani, S.; Perotto, L.; Pires, S.; Radovich, M.; Rubino-Martin, J.-A.; Salvati, L.; Saro, A.; Sartoris, B.; Schellenberger, G.; Streblyanska, A.; Tarrío, P.; Tozzi, P.; Umetsu, K.; van der Burg, R. F. J.; Vazza, F.; Venturi, T.; Yepes, G.; Zarattini, S.; CHEX-MATE Collaboration

Abstract

The Cluster HEritage project with XMM-Newton – Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a three-mega-second Multi-Year Heritage Programme to obtain X-ray observations of a minimally-biased, signal-to-noise-limited sample of 118 galaxy clusters detected by Planck through the Sunyaev–Zeldovich effect. The programme, described in detail in this paper, aims to study the ultimate products of structure formation in time and mass. It is composed of a census of the most recent objects to have formed (Tier-1: 0.05 < z < 0.2; 2 × 10¹⁴ M⊙ < M₅₀₀ < 9 × 10¹⁴ M⊙), together with a sample of the highest mass objects in the Universe (Tier-2: z < 0.6; M₅₀₀ > 7.25 × 10¹⁴ M⊙). The programme will yield an accurate vision of the statistical properties of the underlying population, measure how the gas properties are shaped by collapse into the dark matter halo, uncover the provenance of non-gravitational heating, and resolve the major uncertainties in mass determination that limit the use of clusters for cosmological parameter estimation. We will acquire X-ray exposures of uniform depth, designed to obtain individual mass measurements accurate to 15 − 20% under the hydrostatic assumption. We present the project motivations, describe the programme definition, and detail the ongoing multi-wavelength observational (lensing, SZ, radio) and theoretical effort that is being deployed in support of the project.

Additional Information

© 2021 The CHEX-MATE Collaboration. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Received 9 October 2020; Accepted 10 February 2021. Published online 15 June 2021. The results reported in this article are based on data obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. We thank L. Ballo and XMM Science operation centre for their extensive help in optimising the observations. We thank N. Schartel and B. Wilkes for their support, particularly with regard to the joint Chandra-XMM-Newton programme. Planck (www.esa.int/Planck) was an ESA project with instruments provided by two scientific consortia funded by ESA member states (in particular the lead countries France and Italy), with contributions from NASA (USA) and telescope reflectors provided by a collaboration between ESA and a scientific consortium led and funded by Denmark. The scientific results reported in this article are based in part on observations made by the Chandra X-ray Observatory. This research has made use of the Science Analysis Software (SAS) provided by the XMM SOC and the Chandra X-ray Center (CXC) application packages CIAO, ChIPS, and Sherpa. M.A., G.W.P, I.B, H.A., J.-B.M., A.M.C.L., P.T.. S.Z. acknowledge funding from the European Research Council under the European Union's Seventh Framework Programme (FP72007-2013) ERC grant agreement no 340519. This work has benefitted from CNES and PNCG funding and A.I. acknowledges support from the CNES fellowship program. S.E., M.S., H.B., F.G., M.R., L.L., S.B., I.B., S.D.G., S.G., P.M., S.M., E.R. acknowledge financial contribution from the contracts ASI-INAF Athena 2019-27-HH.0, 'Attività di Studio per la comunità scientifica di Astrofisica delle Alte Energie e Fisica Astroparticellare' (Accordo Attuativo ASI-INAF n. 2017-14-H.0), and from INAF mainstream project 1.05.01.86.10. S.E. acknowledges support from the European Union's Horizon 2020 Programme under the AHEAD2020 project (grant agreement n. 871158). B.J.M. and R.T.D. acknowledge support from STFC grant ST/R000700/1. M.N. is partly supported by INAF-1.05.01.86.20. A.S., L.S. and B.S. are supported by the ERC-StG 'ClustersXCosmo' grant agreement 716762, and by the FARE-MIUR grant 'ClustersXEuclid' R165SBKTMA. A.B. acknowledges support from the ERC Starting Grant 'DRANOEL' n.714245 and from the MIUR grant FARE 'SMS'. S.B. acknowledges also support from the INFN InDark Grant. K.D. acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC-2094 – 3907833. M.D. acknowledges NASA ADAP/SAO Award SV9-89010. M.D.P. acknowledges support from Sapienza Universitá di Roma thanks to Progetti di Ricerca Medi 2019, prot. RM11916B7540DD8D. M.G. acknowledges support from NASA Chandra GO8-19104X/GO9-20114X and HST GO-15890.020-A. M.J. is supported by the United Kingdom Research and Innovation (UKRI) Future Leaders Fellowship 'Using Cosmic Beasts to uncover the Nature of Dark Matter' (grant number MR/S017216/1). F.K. acknowledges support by the French National Research Agency in the framework of the 'Investissements d'avenir program (ANR-15-IDEX-02)'. A.M.C.L.B. acknowledges also funding from a PSL University Research Fellowship. J.A.R.-M. acknowledges support by the Spanish Ministry of Science and Innovation (MICINN) under the projects AYA2014-60438-P and AYA2017-84185-P. K.U. acknowledges support from the Ministry of Science and Technology of Taiwan (grant MOST 109-2112-M-001-018-MY3) and Academia Sinica (grant ASIA-107-M01). F.V. acknowledges financial support from the ERC Starting Grant 'MAGCOW', no.714196. G.Y. acknowledges financial support by MICIU/FEDER (Spain) under project grant PGC2018-094975-C21. CHEX-MATE has benefitted from support from the International Space Science Institute (ISSI) in Bern and we acknowledge ISSI's hospitality. This research made use of a number of python packages, including: astropy (Astropy Collaboration 2018), matplotlib (Hunter 2007), numpy (van der Walt et al. 2011), and scipy (Jones et al. 2001).

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