Extracting the thermal SZ signal from heterogeneous millimeter data sets
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 (Galactic and extragalactic thermal dust) and insrumental 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 combine parametric fitings of the component Spectral Energy Distribution with wavelet and curvelet imaging, but also to deconvolve and combine signals registered with heterogeneous beams. I will show how such techniques allow us to detect substructures in the peripheries of nearby clusters with Planck, and discuss our prospects to extend them to observations performed at lower (Planck all-sky maps) and/or higher angular resolutions (e.g. Planck + SPT).