PIRSA:25110083 Scientific Series Cosmology

DOI10.48660/25110083

Series: Cosmology and Gravitation

Ho, M. (2025). Cosmological Constraints from the High-resolution Lyman-α Forest with PRIYA at k = 1-8 h/Mpc. Perimeter Institute. https://pirsa.org/25110083

Ho, Ming-Feng. Cosmological Constraints from the High-resolution Lyman-α Forest with PRIYA at k = 1-8 h/Mpc. Perimeter Institute, Nov. 11, 2025, https://pirsa.org/25110083 

@misc{ pirsa_PIRSA:25110083,
  doi = {10.48660/25110083},
  url = {https://pirsa.org/25110083},
  author = {Ho, Ming-Feng},
  keywords = {Cosmology},
  language = {en},
  title = {Cosmological Constraints from the High-resolution Lyman-α Forest with PRIYA at k = 1-8 h/Mpc},
  publisher = {Perimeter Institute},
  year = {2025},
  month = {nov},
  note = {PIRSA:25110083 see, \url{https://pirsa.org}}
}

Abstract

We present new cosmological constraints from the small-scale (k ~ 1-8 h/Mpc) Lyman-α forest 1D flux power spectrum (P1D), using high-resolution quasar spectra from XQ-100 and KODIAQ-SQUAD interpreted with the PRIYA simulation-based emulator. The Lyα P1D is a unique probe of structure formation on sub-Mpc scales, sensitive to non-standard dark matter models while also tracing astrophysical processes such as He II reionization and feedback.
 
PRIYA is the first simulation suite to jointly span cosmological parameters and inhomogeneous He II reionization, enabling a full exploration of the covariance between cosmology and astrophysics at these scales. Using this framework, we perform a cosmological inference from XQ-100 and KODIAQ-SQUAD P1D, finding consistent results for XQ-100 with Planck and previous eBOSS analyses, and identifying astrophysical systematics in KODIAQ-SQUAD due to high-column-density absorber selection.
 
High-resolution P1D data provide stronger constraints on IGM thermal history and absorber abundance than medium-resolution surveys, offering complementary information to DESI. This complementarity can help break degeneracies between IGM physics and cosmology in future DESI Lyα forest P1D analyses.

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