BeyondPlanck XIII. Intensity foreground sampling, degeneracies, and priors
Creators: name: Andersen, K. J.
name: Herman, D.
name: Aurlien, R.
name: Banerji, R.
name: Basyrov, A.
name: Bersanelli, M.
name: Bertocco, S.
name: Brilenkov, M.
name: Carbone, M.
name: Colombo, L. P. L.
name: Eriksen, H. K.
name: Eskilt, J. R.
name: Foss, M. K.
name: Franceschet, C.
name: Fuskeland, U.
name: Galeotta, S.
name: Galloway, M.
name: Gerakakis, S.
name: Gjerløw, E.
name: Hensley, B.
name: Iacobellis, M.
name: Ieronymaki, M.
name: Ihle, H. T.
name: Jewell, J. B.
name: Karakci, A.
name: Keihänen, E.
name: Keskitalo, R.
name: Lunde, J. G. S.
name: Maggio, G.
name: Maino, D.
name: Maris, M.
name: Mennella, A.
name: Paradiso, S.
name: Partridge, B.
name: Reinecke, M.
name: San, M.
name: Stutzer, N. -O.
name: Suur-Uski, A. -S.
name: Svalheim, T. L.
name: Tavagnacco, D.
name: Thommesen, H.
name: Watts, D. J.
name: Wehus, I. K.
name: Zacchei, A.
Publisher: name: arXiv
Year: 2022
Subjects: subject: Cosmology and Nongalactic Astrophysics (astro-ph.CO)
subject: FOS: Physical sciences
subject: FOS: Physical sciences

description: We present the intensity foreground algorithms and model employed within the BeyondPlanck analysis framework. The BeyondPlanck analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the $Planck$ Low Frequency Instrument (LFI) data analysis. Given the scope of the BeyondPlanck analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous $\texttt{Commander}$ component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: 1) joint foreground spectral parameter and amplitude sampling, building on ideas from Miramare; 2) component-based monopole determination; 3) joint spectral parameter and monopole sampling; and 4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BeyondPlanck data set is the peak frequency of the anomalous microwave emission component, for which we find $ν_{\mathrm{p}}=25.3\pm0.5$ GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects.
description: 27 pages, 23 figures, 3 tables, part 13 of the BeyondPlanck release. All BeyondPlanck products and software will be released publicly at http://beyondplanck.science. Paper version as accepted by A&amp;A