Speaker
Description
Intensity Mapping (IM) of the 21-cm line of the neutral hydrogen (HI) has become a compelling new technique to map the large-scale structure of the Universe. One of the main challenges is the presence of strong foreground emissions of several orders of magnitude larger than the HI signal. Here we implement a version of the Principal Component Analysis, a blind component-separation technique, based on a kind of spherical wavelets called needlets. These functions exploit double localization both in real and in harmonic space. We test the Need-PCA performances on a set of maps that simulate the SKA AA4 telescope. We compare our results with other component separation methods such as Generalised Morphological Component Analysis (GMCA) and Generalized Needlet Internal Linear Combination (GNILC). All the methods have comparable results. We also test our pipeline in the presence of systematics such as polarization leakage e we find similar results.
| References | to be submitted within end of August |
|---|
