4.6 Article

Simulating intergalactic gas for DESI-like small scale Lymanα forest observations

Journal

Publisher

IOP Publishing Ltd
DOI: 10.1088/1475-7516/2021/04/059

Keywords

cosmological simulations; hydrodynamical simulations; Lyman alpha forest; power spectrum

Funding

  1. PRACE [2019204900, 2010PA4826]
  2. [ANR-16-CE31-0021]

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Measurements of Ly alpha forest based on quasar spectra accurately probe matter distribution on small scales. However, model predictions rely on expensive simulations, limiting previous analyses. With upcoming surveys pushing for higher accuracy, more precise simulations and exploration of parameter space are crucial.
Measurements of the Ly alpha forest based on large numbers of quasar spectra from sky surveys such as SDSS/eBOSS accurately probe the distribution of matter on small scales and thus provide important constraints on several ingredients of the cosmological model. A main summary statistic derived from those measurements is the one-dimensional power spectrum, P-1D, of the Ly alpha absorption. However, model predictions for P-1D rely on expensive hydrodynamical simulations of the intergalactic medium, which was the limiting factor in previous analyses. Datasets from upcoming surveys such as DESI will push observational accuracy near the 1%-level and probe even smaller scales. This observational push mandates even more accurate simulations as well as more careful exploration of parameter space. In this work we evaluate the robustness and accuracy of simulations and the statistical framework used to constrain cosmological parameters. We present a comparison between the grid-based simulation code Nyx and SPH-based code Gadget in the context of P-1D. In addition, we perform resolution and box-size convergence tests using Nyx code. We use a Gaussian process emulation scheme to reduce the number of simulations required for exploration of parameter space without sacrificing the model accuracy. We demonstrate the ability to produce unbiased parameter constraints in an end-to-end inference test using mock eBOSS- and DESI-like data, and we advocate for the usage of adaptive sampling schemes as opposed to using a fixed Latin hypercube design.

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