Impact of Galactic dust non-Gaussianity on searches for B-modes from inflation

Author:

Abril-Cabezas Irene12ORCID,Hervías-Caimapo Carlos3ORCID,von Hausegger Sebastian45ORCID,Sherwin Blake D12,Alonso David5ORCID

Affiliation:

1. Department of Applied Mathematics and Theoretical Physics, University of Cambridge , Cambridge CB3 0WA , UK

2. Kavli Institute for Cosmology, University of Cambridge , Cambridge CB3 0HA , UK

3. Instituto de Astrofísica and Centro de Astro-Ingeniería, Facultad de Física, Pontificia Universidad Católica de Chile , Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago , Chile

4. Department of Physics, University of Oxford, Rudolf-Peierls Centre for Theoretical Physics , Parks Road, OX1 3PU Oxford , UK

5. Department of Physics, University of Oxford, Denys Wilkinson Building , Keble Road, Oxford OX1 3RH , UK

Abstract

ABSTRACT A key challenge in the search for primordial B-modes is the presence of polarized Galactic foregrounds, especially thermal dust emission. Power-spectrum-based analysis methods generally assume the foregrounds to be Gaussian random fields when constructing a likelihood and computing the covariance matrix. In this paper, we investigate how non-Gaussianity in the dust field instead affects CMB and foreground parameter inference in the context of inflationary B-mode searches, capturing this effect via modifications to the dust power-spectrum covariance matrix. For upcoming experiments such as the Simons Observatory, we find no dependence of the tensor-to-scalar ratio uncertainty $\sigma (r)$ on the degree of dust non-Gaussianity or the nature of the dust covariance matrix. We provide an explanation of this result, noting that when frequency decorrelation is negligible, dust in mid-frequency channels is cleaned using high-frequency data in a way that is independent of the spatial statistics of dust. We show that our results hold also for non-zero levels of frequency decorrelation that are compatible with existing data. We find, however, that neglecting the impact of dust non-Gaussianity in the covariance matrix can lead to inaccuracies in goodness-of-fit metrics. Care must thus be taken when using such metrics to test B-mode spectra and models, although we show that any such problems can be mitigated by using only cleaned spectrum combinations when computing goodness-of-fit statistics.

Funder

Fondo Nacional de Desarrollo Científico y Tecnológico

Carlsberg Foundation

European Research Council

Science and Technology Facilities Council

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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