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Bayesian methods for fitting Baryon Acoustic Oscillations in the Lyman-α forest

Cuceu, A; Font-Ribera, A; Joachimi, B; (2020) Bayesian methods for fitting Baryon Acoustic Oscillations in the Lyman-α forest. Journal of Cosmology and Astroparticle Physics , 2020 (7) , Article 035. 10.1088/1475-7516/2020/07/035. Green open access

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Abstract

We study and compare fitting methods for the Lyman-α (Lyα) forest 3D correlation function. We use the nested sampler PolyChord and the community code picca to perform a Bayesian analysis which we compare with previous frequentist analyses. By studying synthetic correlation functions, we find that the frequentist profile likelihood produces results in good agreement with a full Bayesian analysis. On the other hand, Maximum Likelihood Estimation with the Gaussian approximation for the uncertainties is inadequate for current data sets. We compute for the first time the full posterior distribution from the Lyα forest correlation functions measured by the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We highlight the benefits of sampling the full posterior distribution by expanding the baseline analysis to better understand the contamination by Damped Lyα systems (DLAs). We make our improvements and results publicly available as part of the picca package.

Type: Article
Title: Bayesian methods for fitting Baryon Acoustic Oscillations in the Lyman-α forest
Open access status: An open access version is available from UCL Discovery
DOI: 10.1088/1475-7516/2020/07/035
Publisher version: https://doi.org/10.1088/1475-7516/2020/07/035
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10106589
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