Abstract
Aims. We investigate the extent to which foreground-cleaned cosmic microwave background (CMB) maps can be used to estimate cosmological parameters at small scales. Methods. We use the SMICA method, a blind separation technique that works directly at the spectral level. In this work we focus on the small scales of the CMB angular power spectrum, which are chiefly affected by noise and extragalactic foregrounds, such as point sources. We adapt SMICA to use only cross-spectra between data maps, thus avoiding the noise bias. In this study, performed using both simulations and Planck 2015 data, we fit for extragalactic point sources by modelling them as shot noise of two independent populations. Results. In simulations, we correctly recover the point-source emission law, and obtain a CMB angular power spectrum that has an average foreground residual of one fifth of the CMB power at ℓ ≥ 2200. With Planck data, the recovered point-source emission law corresponds to external estimates, with some offsets at the highest and lowest frequencies, possibly due to frequency decoherence of point sources. The CMB angular power spectrum residuals are consistent with what we find in simulations. The cosmological parameters obtained from the simulations and the data show offsets up to 1σ on average from their expected values. Biases on cosmological parameters in simulations represent the expected level of bias in Planck data. Conclusions. The results on cosmological parameters depend on the detail of the foreground residual contamination in the spectrum, and therefore a tailored modelling of the likelihood foreground model is required.
Highlights
The cosmic microwave background (CMB) is an important probe for cosmology, and in recent years a considerable amount of effort has been dedicated to its extraction from available data
We run Monte Carlo Markov chains (MCMC) for fsky = 0.6 on SET3 simulations and obtain cosmological parameters which are consistent with those shown in Fig. 10 within a maximum of 0.022σ (σ here is the scatter of the marginal mean among various simulations)
We have studied a new configuration of the spectral matching ICA (SMICA) method to estimate the CMB angular power spectrum directly via component separation
Summary
The cosmic microwave background (CMB) is an important probe for cosmology, and in recent years a considerable amount of effort has been dedicated to its extraction from available data. We focus on the first step of spectral fitting, that is, the SMICA method is only used as a tool for the joint fit of all the auto- and cross-spectra of a set of frequency channels In this way the CMB angular power spectrum is estimated directly from the data. The natural comparison to make is that of the results of this work with those of the cosmological analysis of the Planck collaboration (Planck Collaboration XI 2016; Planck Collaboration XIII 2016) Their high- likelihood (PlikTT) is based on the spectra of a few frequency channels with low foreground content, in the cleaner area of the sky, and on a tailored scale range.
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