Orateur
Description
The measurement of primordial CMB B-mode polarization is fundamentally limited by our ability to separate this faint signal from bright and complex Galactic foregrounds. Spectral Matching Independent Component Analysis (SMICA) offers a flexible, semi-blind approach to this foreground-cleaning problem. However, its standard implementation relies on a physically unrealistic assumption of non-spatially varying foreground emission, reducing the efficiency of the method. In this work, we develop two complementary strategies to address this limitation at the component-separation level. First, we augment SMICA with effective foreground components beyond the physical dust and synchrotron degrees of freedom. Second, we extend SMICA to operate independently on subsets of the sky, better capturing local variations in the foreground emission. Beyond component separation, we further explore a likelihood-level marginalization procedure using internally reconstructed foreground templates. We demonstrate the performance of the pipeline on simulated LiteBIRD-like observations, using foreground models of increasing complexity based on d1s1 and d10s5. However, as this newly proposed approach is fundamentally limited by a methodological so-called ILC bias, we will also introduce and validate a new global, consistent, maximum-likelihood framework: “Map-based Inference of Spectral Templates with Independent Component Analysis” (MISTICA). This new method follows the core principle of SMICA, retaining the spectral-diversity-based separation within a global likelihood framework, providing a direct estimate of the power spectrum, while allowing for natural incorporation of a spatially varying mixing matrix and handling of partial/cut-sky coverage.