Successive releases of Planck data have demonstrated the strength of the Sunyaev-Zeldovich (SZ) effect in detecting hot baryons out to the galaxy cluster peripheries. To infer the hot gas pressure structure from nearby galaxy clusters to more distant objects, we developed a parametric method that models the spectral energy distribution and spatial anisotropies of both the Galactic thermal dust and the Cosmic Microwave Background, that are mixed-up with the cluster SZ and dust signals. Taking advantage of the best angular resolution of the High Frequency Instrument channels (5 arcmin) and using X-ray priors in the innermost cluster regions that are not resolved with Planck, this modelling allowed us to analyze a sample of 61 nearby members of the Planck catalog of SZ sources (0 < z < 0.5,z = 0.15) using the full mission data, as well as to examine a distant sample of 23 clusters (0.5 < z < 1,z = 0.56) that have been recently followed-up with XMM-Newton and Chandra observations. We find that (i) the average shape of the mass-scaled pressure profiles agrees with results obtained by the Planck collaboration in the nearby cluster sample, and that (ii) no sign of evolution is discernible between averaged pressure profiles of the low-and high-redshift cluster samples. In line with theoretical predictions for these halo masses and redshift ranges, the dispersion of individual profiles relative to a self-similar shape stays well below 10 % inside r 500 but increases in the cluster outskirts.

The possibility of determining the value of the Hubble constant using observations of galaxy clusters in X-ray and microwave wavelengths through the Sunyaev Zel'dovich (SZ) effect has long been known. Previous measurements have been plagued by relatively large errors in the observational data and severe biases induced, for example, by cluster triaxiality and clumpiness. The advent of Planck allows us to map the Compton parameter y, that is, the amplitude of the SZ effect, with unprecedented accuracy at intermediate cluster-centric radii, which in turn allows performing a detailed spatially resolved comparison with X-ray measurements. Given such higher quality observational data, we developed a Bayesian approach that combines informed priors on the physics of the intracluster medium obtained from hydrodynamical simulations of massive clusters with measurement uncertainties. We applied our method to a sample of 61 galaxy clusters with redshifts up to z < 0.5 observed with Planck and XMM-Newton and find H 0 = 67 ± 3km s −1 Mpc −1 .

Complementarily to X-ray observations, the thermal SZ effect is a powerful tool to probe the baryonic content of galaxy clusters from their core to their peripheries. While contaminations by astrophysical and instrumental backgrounds require us to scan the thermal SZ signal across various frequencies, the multi-scale nature of cluster morphologies require us to observe such objects at various angular resolutions. We developed component separation algorithms that take advantage of sparse representations to combine these heterogeneous pieces of information, separate the thermal SZ signal from its contaminants, detect and map the thermal SZ signal of galaxy clusters from nearby to more distant clusters of the Planck catalogue. Spatially weighted likelihoods allow us in particular to connect parametric fittings of the component Spectral Energy Distribution with wavelet and curvelet imaging, but also to combine signals registered with beams of various width. Such techniques already allow us to detect sub-structures in the peripheries of nearby clusters with Planck, and could be extended to observations performed at higher angular resolutions.