BeyondPlanck XV. Polarized foreground emission between 30 and 70 GHz
T. L. Svalheim, K. J. Andersen, R. Aurlien, R. Banerji, M. Bersanelli,, S. Bertocco, M. Brilenkov, M. Carbone, L. P. L. Colombo, H. K. Eriksen, M. K., Foss, C. Franceschet, U. Fuskeland, S. Galeotta, M. Galloway, S. Gerakakis,, E. Gjerl{\o}w, B. Hensley, D. Herman, M. Iacobellis

TL;DR
This study constrains polarized foreground emission between 30 and 70 GHz using combined Planck LFI and WMAP data within a Bayesian framework, implementing multi-resolution component separation for the first time in CMB analysis.
Contribution
It introduces a novel multi-resolution component separation method applied to CMB data, jointly analyzing amplitude and spectral energy distribution parameters across multiple frequencies.
Findings
Spectral indices for synchrotron emission in different regions are consistent with previous results.
Thermal dust spectral index is slightly steeper than previous Planck HFI estimates but statistically compatible.
High Latitude region is prior-dominated, while Galactic Center shows residual systematics.
Abstract
We constrain polarized foreground emission between 30 and 70 GHz with the Planck Low Frequency Instrument (LFI) and WMAP data within the global Bayesian BeyondPlanck framework. We combine for the first time full-resolution Planck LFI time-ordered data with low-resolution WMAP sky maps at 33, 40 and 61 GHz. Spectral parameters are fit with a likelihood defined at the native resolution of each frequency channel. This analysis represents the first implementation of true multi-resolution component separation applied to CMB observations for both amplitude and spectral energy distribution (SED) parameters. For synchrotron emission, we approximate the SED as a power-law in frequency and find that the low signal-to-noise ratio of the current data strongly limits the number of free parameters that may be robustly constrained. We partition the sky into four large disjoint regions (High Latitude;…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling
