http://arxiv.org/abs/2205.13968
We present a Bayesian parametric component separation method for polarised microwave sky maps. We solve jointly for the primary cosmic microwave background (CMB) signal and the main Galactic polarised foreground components. For the latter, we consider electron-synchrotron radiation and thermal dust emission, modelled in frequency as a power law and a modified blackbody respectively. We account for inter-pixel correlations in the noise covariance matrices of the input maps and introduce a spatial correlation length in the prior matrices for the spectral indices beta. We apply our method to low-resolution polarised Planck 2018 Low and High Frequency Instrument (LFI/HFI) data, including the SRoll2 re-processing of HFI data. We find evidence for spatial variation of the synchrotron spectral index, and no evidence for depolarisation of dust. Using the HFI SRoll2 maps, and applying wide priors on the spectral indices, we find a mean polarised synchrotron spectral index over the unmasked sky of beta-sync = -2.833 +- 0.620. For polarised dust emission, we obtain beta-dust = 1.429 +- 0.236. Our method returns correlated uncertainties for all components of the sky model. Using our recovered CMB maps and associated uncertainties, we constrain the optical depth to reionization, tau, using a cross-spectrum-based likelihood-approximation scheme (momento) to be tau = 0.0598 +- 0.0059. We confirm our findings using a pixel-based likelihood (pixlike). In both cases, we obtain a result that is consistent with, albeit a fraction of a sigma higher than, that found by subtracting spatially uniform foreground templates. While the latter method is sufficient for current polarisation data from Planck, next-generation space-borne CMB experiments will need more powerful schemes such as the one presented here.
R. Belsunce, S. Gratton and G. Efstathiou
Mon, 30 May 22
24/47
Comments: 12 pages, 11 figures
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