Recovery of 21 cm intensity maps with sparse component separation

Understand

21 cm intensity mapping has emerged as a promising technique to map the large-scale structure of the Universe.

• However, the presence of foregrounds with amplitudes orders of magnitude larger than the cosmological signal constitutes a critical challenge.
• Here, we test the sparsity-based algorithm Generalised Morphological Component Analysis (GMCA) as a blind component separation technique for this class of experiments.
• We test the GMCA performance against realistic full-sky mock temperature maps that include, besides astrophysical foregrounds, also a fraction of the polarized part of the signal leaked into the unpolarized one, a very troublesome foreground to subtract, usually referred to as polarization leakage.