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Title: Synthetic spectra for Lyman-α forest analysis in the Dark Energy Spectroscopic Instrument

Journal Article · · Journal of Cosmology and Astroparticle Physics
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Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-α quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use a synthetic dataset to forecast the BAO scale constraining power of the completed DESI survey through the Lyman-α forest.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Univ. of Utah, Salt Lake City, UT (United States)
Sponsoring Organization:
National Science Foundation (NSF); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), High Energy Physics (HEP)
Contributing Organization:
DESI Collaboration
Grant/Contract Number:
AC02-05CH11231; SC0009959
OSTI ID:
3009745
Journal Information:
Journal of Cosmology and Astroparticle Physics, Journal Name: Journal of Cosmology and Astroparticle Physics Journal Issue: 01 Vol. 2025; ISSN 1475-7516
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English

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