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arxiv: 2401.00303 · v3 · pith:GB5A2BQBnew · submitted 2023-12-30 · 🌌 astro-ph.CO

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

Hiram K. Herrera-Alcantar , Andrea Mu\~noz-Guti\'errez , Ting Tan , Alma X. Gonz\'alez-Morales , Andreu Font-Ribera , Julien Guy , John Moustakas , David Kirkby
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E. Armengaud A. Bault L. Cabayol-Garcia J. Chaves-Montero A. Cuceu R. de la Cruz L. \'A. Garc\'ia C. Gordon V. Ir\v{s}i\v{c} N. G. Kara\c{c}ayl{\i} J. M. Le Goff P. Montero-Camacho G. Niz I. P\'erez-R\`afols C. Ram\'irez-P\'erez C. Ravoux M. Walther J. Aguilar S. Ahlen D. Brooks T. Claybaugh K. Dawson A. de la Macorra P. Doel J. E. Forero-Romero E. Gazta\~naga S. Gontcho A Gontcho K. Honscheid R. Kehoe T. Kisner M. Landriau Michael E. Levi M. Manera P. Martini A. Meisner R. Miquel J. Nie N. Palanque-Delabrouille C. Poppett M. Rezaie G. Rossi E. Sanchez H. Seo G. Tarl\'e B. A. Weaver Z. Zhou
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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-$\alpha$ 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 full survey synthetic data to forecast the BAO scale constraining power with DESI.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations

    astro-ph.CO 2024-04 accept novelty 7.0

    First-year DESI BAO data are consistent with flat LambdaCDM and, when combined with CMB, show a 2.5-3.9 sigma preference for evolving dark energy (w0 > -1, wa < 0) that strengthens with certain supernova datasets.

  2. DESI 2024 IV: Baryon Acoustic Oscillations from the Lyman Alpha Forest

    astro-ph.CO 2024-04 accept novelty 6.0

    DESI measures BAO from the Lyα forest at z_eff=2.33, reporting H(z) = (239.2 ± 4.8) (147.09 Mpc/rd) km/s/Mpc and DM(z) = (5.84 ± 0.14) (rd/147.09 Mpc) Gpc.

  3. DESI DR2 Results I: Baryon Acoustic Oscillations from the Lyman Alpha Forest

    astro-ph.CO 2025-03 accept novelty 4.0

    DESI DR2 delivers 0.65% precision BAO measurements from the LyA forest at z_eff=2.33, with D_H/r_d = 8.632 ± 0.098 ± 0.026 and D_M/r_d = 38.99 ± 0.52 ± 0.12.

  4. Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest

    astro-ph.CO 2026-05 unverdicted novelty 2.0

    Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.