All-sky modelling requirements for Bayesian 21 cm power spectrum estimation with bayeseor

Author:

Burba Jacob12ORCID,Sims Peter H34ORCID,Pober Jonathan C2

Affiliation:

1. Department of Physics and Astronomy, University of Manchester , M13 9PL Manchester, UK

2. Department of Physics, Brown University , Providence, RI 02912, USA

3. McGill Space Institute, McGill University , 3550 University Street, Montreal, QC H3A 2A7, Canada

4. Department of Physics, McGill University , 3600 University Street, Montreal, QC H3A 2T8, Canada

Abstract

ABSTRACT We present a comprehensive simulation-based study of the bayeseor code for 21 cm power spectrum recovery when analytically marginalizing over foreground parameters. To account for covariance between the 21 cm signal and contaminating foreground emission, bayeseor jointly constructs models for both signals within a Bayesian framework. Due to computational constraints, the forward model is constructed using a restricted field of view (FoV) in the image domain. When the only Epoch of Reionization contaminants are noise and foregrounds, we demonstrate that bayeseor can accurately recover the 21 cm power spectrum when the component of sky emission outside this forward-modelled region is downweighted by the beam at the level of the dynamic range between the foreground and 21 cm signals. However, when all-sky foreground emission is included along with a realistic instrument primary beam with sidelobes above this threshold extending to the horizon, the recovered power spectrum is contaminated by unmodelled sky emission outside the restricted FoV model. Expanding the combined cosmological and foreground model to cover the whole sky is computationally prohibitive. To address this, we present a modified version of bayeseor that allows for an all-sky foreground model, while the modelled 21 cm signal remains only within the primary FoV of the telescope. With this modification, it will be feasible to run an all-sky bayeseor analysis on a sizeable compute cluster. We also discuss several future directions for further reducing the need to model all-sky foregrounds, including wide-field foreground subtraction, an image-domain likelihood utilizing a tapering function, and instrument primary beam design.

Funder

National Science Foundation

National Aeronautics and Space Administration

McGill Space Institute

European Research Council

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. 21-cm foreground removal using AI and the frequency-difference technique;Physical Review D;2024-03-05

2. Improved Foreground Modelling for Bayesian 21 cm Power Spectrum Estimation with BayesEoR;2023 XXXVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS);2023-08-19

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