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3D Correlations in the Lyman-α Forest from Early DESI Data

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arxiv 2308.10950 v1 pith:LFSLJ4BC submitted 2023-08-21 astro-ph.CO

3D Correlations in the Lyman-α Forest from Early DESI Data

Calum Gordon , Andrei Cuceu , Jon\'as Chaves-Montero , Andreu Font-Ribera , Alma Xochitl Gonz\'alez-Morales , J. Aguilar , S. Ahlen , E. Armengaud
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S. Bailey A. Bault A. Brodzeller D. Brooks T. Claybaugh R. de la Cruz K. Dawson P. Doel J. E. Forero-Romero S. Gontcho A Gontcho J. Guy H. K. Herrera-Alcantar V. Ir\v{s}i\v{c} N. G. Kara\c{c}ayl{\i} D. Kirkby M. Landriau L. Le Guillou M. E. Levi A. de la Macorra M. Manera P. Martini A. Meisner R. Miquel P. Montero-Camacho A. Mu\~noz-Guti\'errez L. Napolitano J. Nie G. Niz N. Palanque-Delabrouille W. J. Percival M. Pieri C. Poppett F. Prada I. P\'erez-R\`afols C. Ram\'irez-P\'erez C. Ravoux M. Rezaie A. J. Ross G. Rossi E. Sanchez D. Schlegel M. Schubnell H. Seo F. Sinigaglia T. Tan G. Tarl\'e M. Walther B. A. Weaver C. Y\`eche Z. Zhou H. Zou
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We present the first measurements of Lyman-$\alpha$ (Ly$\alpha$) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Ly$\alpha$ absorption using 88,509 quasars at $z>2$, and its cross-correlation with quasars using a further 147,899 tracer quasars at $z\gtrsim1.77$. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of $3.8\sigma$, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. We validate the existing analysis methods of Ly$\alpha$ correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.

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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. DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

    astro-ph.CO 2024-04 accept novelty 7.0

    DESI measures BAO scales in six redshift bins with 0.52% combined precision using 5.7 million objects, detecting the signal at up to 9.1 sigma and finding larger scales than Planck LCDM at z<0.8.

  3. Lyman-Alpha Forest and its Cross-Correlation with High-Redshift Galaxies in Effective Field Theory at the Field Level

    astro-ph.CO 2026-06 unverdicted novelty 6.0

    An EFT-based field-level forward model for the Lyman-alpha forest matches simulations at the percent level on quasi-linear scales and generates mocks for DESI and DESI-II analyses.

  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.