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.
Hydrodynamical simulations of the Lyman-Alpha forest: data comparisons
2 Pith papers cite this work. Polarity classification is still indexing.
abstract
Numerical hydrodynamical simulations are used to predict the expected absorption properties of the Lyman-Alpha forest for a variety of Cold Dark Matter dominated cosmological scenarios: CHDM, OCDM, LCDM, SCDM, and tCDM. Synthetic spectra are constructed duplicating the resolution, signal-to-noise ratio, and wavelength coverage of several published high resolution spectra, and their statistical properties compared on the basis of the flux distribution of the spectra, the distribution of coefficients in a wavelet decomposition of the spectra, and the distributions of absorption line profile parameters. Agreement between the measured and predicted cumulative distributions is found at the few to several percent level. The best-fitting models to the flux distribution correspond to normalizations on the scale of the cosmological Jeans length of 1.3 < sigma_J < 1.7 at z=3. No single model provides an acceptable match to all the distributions. Larger median Doppler parameters are found in the measured spectra than predicted by all but the lowest normalization models (CHDM and tCDM), which provide poor fits to the flux distributions. The discrepancy in Doppler parameters is particularly large for absorption systems optically thin at the Lyman-Alpha line-centre. This may indicate the need to introduce additional energy injection throughout the IGM, as may be provided by late HeII reionization (z_HeII~3.5) or supernovae-driven winds from young galaxies. The models require a hydrogen ionization rate at redshifts 1.7<z<3.5 within a factor of 2 of that predicted from QSOs alone as the sources of the UV photoionization background, although with a slower rate of decline with redshift at z>3.5 than predicted from current QSO counts.
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astro-ph.CO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
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Lyman-Alpha Forest and its Cross-Correlation with High-Redshift Galaxies in Effective Field Theory at the Field Level
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.
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Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.