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Date du début: 1 avr. 2014, Date de fin: 31 mars 2019 PROJET  TERMINÉ 

"Our project aims at testing the standard LCDM scenario for the formation of collapsed structures. Taking advantage of the advent of cluster detection via the SZ effect, we will use the most massive clusters of galaxies and their evolution as laboratory. We build on the Planck SZ survey, the first All Sky survey since the RASS X-ray survey. We will substantially extend the nominal Planck cluster catalogue by developing novel detection techniques based on a simultaneous search of objects in Planck and RASS maps, reaching lower masses and higher redshifts, while keeping a high catalogue purity.For the first time, we will have the sample size, redshift leverage, and completeness, for a decisive test of the standard LCDM model of the dark matter gravitational collapse on cluster scale. The test will be provided by a full statistical analysis of the dark matter profiles and their evolution. The X-ray technique to derive mass profile will be extended to the full cluster population. This will be made possible by an integrated approach involving systematic confrontation of observations with tailor-made numerical simulations.Using multi-wavelength data and simulations, we will also assess the dynamical behaviour of the baryons as they collect in dark matter potential. We will i) provide the first complete census of the dark matter, hot and cold baryons and its evolution ii) quantify the thermo- dynamical state up to z~1 as a probe of hierarchical structure formation and gravitational heating iii) probe the link between non-thermal and thermal components.The project will either cement our current understanding of the dark matter collapse, a prerequisite to any assessment of the specific baryon physics, or points towards the need for revision of the current paradigm, with important cosmological implications. The new detection techniques will be applicable to future surveys. Lastly, we will provide a ‘gold sample’ of galaxy clusters, ideal for cosmological parameter estimate."