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Improved Galactic Foreground Removal for B-Modes Detection with Clustering Methods

Characterizing the sub-mm Galactic emission has become increasingly critical especially in identifying and removing its polarized contribution from the one emitted by the Cosmic Microwave Background (CMB). In this work, we present a parametric foreground removal performed onto sub-patches identified in the celestial sphere by means of spectral clustering. Our approach takes into account efficiently both the geometrical affinity and the similarity induced by the measurements and the accompanying errors. The optimal partition is then used to parametrically separate the Galactic emission encoding thermal dust and synchrotron from the CMB one applied on two nominal observations of forthcoming experiments from the ground and from the space. Performing the parametric fit singularly on each of the clustering derived regions results in an overall improvement: both controlling the bias and the uncertainties in the CMB $B-$mode recovered maps. We finally apply this technique using the map of the number of clouds along the line of sight, $\mathcal{N}_c$, as estimated from HI emission data and perform parametric fitting onto patches derived by clustering on this map. We show that adopting the $\mathcal{N}_c$ map as a tracer for the patches related to the thermal dust emission, results in reducing the $B-$mode residuals post-component separation. The code is made publicly available.