2015/07/16 by M.-A. Bigot-Sazy, M. -A. Bigot-Sazy, C. Dickinson +9 · 1 citation
Physics and Astronomy · #Acoustics #Artificial intelligence #Astrophysics #Astrophysics and Cosmic Phenomena #Background noise #Galaxies: Formation, Evolution, Phenomena #Galaxy #Intensity mapping #Noise (video) #Optics #Parametric model #Parametric statistics #Physics #Principal component analysis #Radio Astronomy Observations and Technology #Redshift #Sky #Statistics #astro-ph.CO #astro-ph.IM
paper · pdf · doi:10.1093/mnras/stv2153
14 pages, 12 figures. Submitted to MNRAS
arxiv created 2015/07/16 · openalex publication_date 2015/10/17 · arxiv updated 2015/10/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
H i intensity mapping is an emerging tool to probe dark energy. Observations of the redshifted H i signal will be contaminated by instrumental noise, atmospheric and Galactic foregrounds. The latter is expected to be four orders of magnitude brighter than the H i emission we wish to detect. We present a simulation of single-dish observations including an instrumental noise model with 1/f and white noise, and sky emission with a diffuse Galactic foreground and H i emission. We consider two foreground cleaning methods: spectral parametric fitting and principal component analysis. For a smooth frequency spectrum of the foreground and instrumental effects, we find that the parametric fitting method provides residuals that are still contaminated by foreground and 1/f noise, but the principal component analysis can remove this contamination down to the thermal noise level. This method is robust for a range of different models of foreground and noise, and so constitutes a promising way to recover the H i signal from the data. However, it induces a leakage of the cosmological signal into the subtracted foreground of around 5 per cent. The efficiency of the component separation methods depends heavily on the smoothness of the frequency spectrum of the foreground and the 1/f noise. We find that as long as the spectral variations over the band are slow compared to the channel width, the foreground cleaning method still works.