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The Lyman-α forest catalog from the Dark Energy Spectroscopic Instrument Early Data Release

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arxiv 2306.06312 v6 pith:FPMLQZMC submitted 2023-06-09 astro-ph.CO

The Lyman-α forest catalog from the Dark Energy Spectroscopic Instrument Early Data Release

C\'esar Ram\'irez-P\'erez , Ignasi P\'erez-R\`afols , Andreu Font-Ribera , Marie Lynn Abdul-Karim , E. Armengaud , J. Bautista , S. F. Beltran , L. Cabayol-Garcia
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Z. Cai S. Chabanier E. Chaussidon J. Chaves-Montero A. Cuceu R. de la Cruz J. Garc\'ia-Bellido A. X. Gonzalez-Morales C. Gordon H. K. Herrera-Alcantar V. Ir\v{s}i\v{c} M. Ishak N. G. Kara\c{c}ayl{\i} Zarija Luki\'c C. J. Manser P. Montero-Camacho L. Napolitano G. Niz M. Pieri C. Ravoux F. Sinigaglia T. Tan M. Walther B. Wang J. Aguilar S. Ahlen S. Bailey D. Brooks T. Claybaugh K. Dawson A. de la Macorra G. Dhungana P. Doel K. Fanning J. E. Forero-Romero S. Gontcho A Gontcho J. Guy K. Honscheid R. Kehoe T. Kisner M. Landriau L. Le Guillou M. E. Levi C. Magneville P. Martini A. Meisner R. Miquel J. Moustakas E. Mueller A. Mu\~noz-Guti\'errez J. Nie N. Palanque-Delabrouille W. J. Percival G. Rossi E. Sanchez E. F. Schlafly D. Schlegel H. Seo G. Tarl\'e B. A. Weaver C. Y\`eche Z. Zhou
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We present and validate the catalog of Lyman-$\alpha$ forest fluctuations for 3D analyses using the Early Data Release (EDR) from the Dark Energy Spectroscopic Instrument (DESI) survey. We used 88,511 quasars collected from DESI Survey Validation (SV) data and the first two months of the main survey (M2). We present several improvements to the method used to extract the Lyman-$\alpha$ absorption fluctuations performed in previous analyses from the Sloan Digital Sky Survey (SDSS). In particular, we modify the weighting scheme and show that it can improve the precision of the correlation function measurement by more than 20%. This catalog can be downloaded from https://data.desi.lbl.gov/public/edr/vac/edr/lya/fuji/v0.3 and it will be used in the near future for the first DESI measurements of the 3D correlations in the Lyman-$\alpha$ forest.

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Cited by 6 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. Alcock-Paczynski Blinding Scheme for the Ly-$\alpha$ Forest Analysis

    astro-ph.CO 2026-07 accept novelty 6.0

    A catalog-level Alcock-Paczynski wavelength-shift blinding scheme for the Lyman-alpha forest robustly hides the expansion history and correctly shifts the BAO peak on DESI DR1 data and mocks.

  3. Probing the limits of cosmological information from the Lyman-$\alpha$ forest 2-point correlation functions

    astro-ph.CO 2025-09 unverdicted novelty 6.0

    Using idealized synthetic data, knowing the true continuum in Lyα forest auto- and cross-correlations reduces uncertainties on the AP parameter and Ω_m by ~10%, with extension to 240 h^{-1}Mpc scales adding up to ~15%...

  4. 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.

  5. 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.

  6. 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.