Planck LFI : Comparison Between Galaxy Straylight Contamination and other Systematic Effects

The straylight contamination due to the Galactic emission (GSC, Galaxy Straylight Contamination) entering at large angles from the antenna centre direction may be one of the most critical sources of systematic effects in observations of the cosmic microwave background (CMB) anisotropies by future satellite missions like Planck and MAP. For the Low Frequency Instrument (LFI), this effect is expected to be particularly crucial at the lowest frequency channels. We describe here different methods to evaluate the impact of this effect and compare it with other systematics of instrumental and astrophysical origin. The results are presented in terms of simulated data streams and maps, Fourier series decomposition and angular power spectrum. The contributions within few degrees from the beam centre dominate the GSC near the Galaxy plane. The antenna sidelobes at intermediate and large angles from the beam centre dominate the GSC at medium and high Galactic latitudes. We find a GSC peak at ∼ 15µK and a GSC angular power spectrum above that of the white noise for multipoles ℓ < ∼ 10 albeit smaller than that of CMB anisotropies by a factor larger than ∼ 10. At large mul-tipoles, the GSC affects the determination of CMB angular power spectrum significantly less than other kinds of instrumental systematics, like main beam distortions and 1/f noise. Although the GSC is largest at low Galac-tic latitudes, the contamination produced by far pattern features at medium and high Galactic latitudes, peak-ing at ∼ 4µK, has to be carefully investigated, because the combination of low amplitude of Galaxy emission in those regions with the extremely good nominal Planck sensitivity naturally makes high Galactic latitude areas the targets for unprecedentedly precise estimation of cosmological CMB anisotropy. This paper is based on Planck LFI activities. Key words: Cosmology: cosmic microwave background – Galaxy: general – Space vehicles – Telescopes – Methods: data analysis