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

被引:6
作者
Abril-Cabezas, Irene [1 ,2 ]
Hervias-Caimapo, Carlos [3 ]
von Hausegger, Sebastian [4 ,5 ]
Sherwin, Blake D. [1 ]
Alonso, David [5 ]
机构
[1] Univ Cambridge, Dept Appl Math & Theoret Phys, Cambridge CB3 0WA, England
[2] Univ Cambridge, Kavli Inst Cosmol, Cambridge CB3 0HA, England
[3] Pontificia Univ Catolica Chile, Fac Fis, Inst Astrofis, Av Vicuna Mackenna 4860, Santiago 7820436, Chile
[4] Univ Oxford, Rudolf Peierls Ctr Theoret Phys, Dept Phys, Parks Rd, Oxford OX1 3PU, England
[5] Univ Oxford, Dept Phys, Denys Wilkinson Bldg,Keble Rd, Oxford OX1 3RH, England
基金
欧洲研究理事会; 英国科学技术设施理事会;
关键词
methods: data analysis; cosmic background radiation; cosmological parameters; diffuse radiation; COMPONENT SEPARATION; POWER SPECTRUM; STATISTICAL PROPERTIES; FULL-SKY; POLARIZATION; EMISSION; PROBE; SUBMILLIMETER; FOREGROUNDS; RADIATION;
D O I
10.1093/mnras/stad3529
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
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.
引用
收藏
页码:5751 / 5766
页数:16
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