Foreground removal and 21 cm signal estimates: comparing different blind methods for the BINGO Telescope

Abstract

The BINGO radiotelescope will observe hydrogen distribution using Intensity Mapping (IM) to analyze the Dark Energy paradigm through Baryon Acoustic Oscillations. The target signal is contaminated by unwanted signals and instrumental noise, making accurate estimations essential for characterizing the 21 cm signal. In this study, we evaluated the performance of three blind foreground-removing algorithms - FastICA, GNILC, and GMCA - on the BINGO pipeline. Each method used different approaches to estimate foreground contributions, and we also investigated how the number of simulations for debiasing affects estimation quality. Our findings indicate that using 50 or 400 simulations yields equivalent results at this stage of analysis. All algorithms produced statistically consistent estimates of the 21 cm signal. We used FastICA for estimating and debiasing the HI spectra from five years of observations, which yielded reliable results, although the first channel was affected by edge effects from the mixing matrix. The overall signal-to-noise ratio was 204, and the chi-squared value was 1.8.