BEYONDPLANCK

XIII. Intensity foreground sampling, degeneracies, and priors

¹ Institute of Theoretical Astrophysics, University of Oslo, Sem Sælands vei 13, 0371 Oslo, Norway
e-mail: k.j.andersen@astro.uio.no; andersen.kristian.joten@gmail.com
² Dipartimento di Fisica, Università degli Studi di Milano, Via Celoria, 16, Milano, Italy
³ INAF-IASF Milano, Via E. Bassini 15, Milano, Italy
⁴ INFN, Sezione di Milano, Via Celoria 16, Milano, Italy
⁵ INAF-Osservatorio Astronomico di Trieste, Via G.B. Tiepolo 11, Trieste, Italy
⁶ Planetek Hellas, Leoforos Kifisias 44, Marousi, 151 25 Greece
⁷ Department of Astrophysical Sciences, Princeton University, Princeton, NJ, 08544 USA
⁸ Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA, USA
⁹ Department of Physics, Gustaf Hällströmin katu 2, University of Helsinki, Helsinki, Finland
¹⁰ Helsinki Institute of Physics, Gustaf Hällströmin katu 2, University of Helsinki, Helsinki, Finland
¹¹ Computational Cosmology Center, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
¹² Haverford College Astronomy Department, 370 Lancaster Avenue, Haverford, PA, USA
¹³ Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Str. 1, 85741 Garching, Germany
¹⁴ Dipartimento di Fisica, Università degli Studi di Trieste, Via A. Valerio 2, Trieste, Italy

Received: 25 January 2022
Accepted: 29 August 2022

Abstract

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 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_p = 25.3 ± 0.5 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. This work will be organized within the Open Science-based COSMOGLOBE community effort.