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Journal article : Review

LyaCoLoRe: synthetic datasets for current and future Lyman-α forest BAO surveys

Abstract:
The statistical power of Lyman-α forest Baryon Acoustic Oscillation (BAO) measurements is set to increase significantly in the coming years as new instruments such as the Dark Energy Spectroscopic Instrument deliver progressively more constraining data. Generating mock datasets for such measurements will be important for validating analysis pipelines and evaluating the effects of systematics. With such studies in mind, we present LyaCoLoRe: A package for producing synthetic Lyman-α forest survey datasets for BAO analyses. LyaCoLoRe transforms initial Gaussian random field skewers into skewers of transmitted flux fraction via a number of fast approximations. In this work we explain the methods of producing mock datasets used in LyaCoLoRe, and then measure correlation functions on a suite of realisations of such data. We demonstrate that we are able to recover the correct BAO signal, as well as large-scale bias parameters similar to literature values. Finally, we briefly describe methods to add further astrophysical effects to our skewers-high column density systems and metal absorbers-which act as potential complications for BAO analyses.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1088/1475-7516/2020/03/068

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Publisher:
IOP Publishing
Journal:
Journal of Cosmology and Astroparticle Physics More from this journal
Volume:
2020
Issue:
3
Article number:
68
Publication date:
2020-03-31
Acceptance date:
2020-03-02
DOI:
EISSN:
1475-7516


Language:
English
Keywords:
Subtype:
Review
Pubs id:
1112953
Local pid:
pubs:1112953
Deposit date:
2021-06-06
ARK identifier:

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