Gaussian Process Regression for foreground removal in HI intensity mapping experiments
We apply for the first time Gaussian Process Regression (GPR) as a foreground removal technique in the context of single-dish, low redshift HI intensity mapping, and present an open-source python toolkit for doing so. We use MeerKAT and SKA1-MID-like simulations of 21cm foregrounds (including polarisation leakage), HI cosmological signal and instrumental noise. We find that …