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Modeling the Cosmological Lyman-α Forest at the Field Level.

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We developed an analytic model to predict the Lyman-alpha (Ly-α) forest, crucial for understanding the intergalactic medium and cosmology. This model accurately reproduces simulation results, enabling better analysis of quasar spectra.

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Area of Science:

  • Cosmology
  • Astrophysics
  • Intergalactic Medium

Background:

  • The Lyman-alpha (Ly-α) forest, a series of absorption lines in quasar spectra, is vital for probing the intergalactic medium and cosmology at high redshifts.
  • Current redshift surveys require precise theoretical tools to accurately model the Ly-α forest's complex distribution.

Purpose of the Study:

  • To develop an analytic, perturbative forward model for predicting the Ly-α forest at the field level.
  • To provide precise theoretical tools for analyzing large-scale structure and cosmological parameters from Ly-α forest data.

Main Methods:

  • Developed an analytic, perturbative forward model to predict Ly-α forest flux.
  • Compared model predictions against the Sherwood hydrodynamic simulations.
  • Evaluated the model's performance on the Ly-α forest flux power spectrum, its cross-correlation with dark matter halos, and the one-point probability distribution function.

Main Results:

  • The analytic model demonstrates remarkable agreement with hydrodynamic simulations.
  • The model reproduces key Ly-α forest statistics, including the flux power spectrum and cross-correlation with dark matter halos, at the percent level.
  • Accuracy extends down to scales of a few Megaparsecs.

Conclusions:

  • The developed model effectively bridges analytic predictions on large scales with simulation accuracy on small scales.
  • This work provides essential tools for field-level inference from Ly-α forest data and simulation-based cosmological priors.
  • The model is timely for maximizing the scientific return from instruments like the Dark Energy Spectroscopic Instrument (DESI).