Review of 21 cm forest observations as a probe of the epoch of reionization and fundamental physics using the Square Kilometre Array.
The Lyman-alpha Forest as a Cosmological Tool
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abstract
We review recent developments in the theory of the Lyman-alpha forest and their implications for the role of the forest as a test of cosmological models. Simulations predict a relatively tight correlation between the local Lya optical depth and the local gas or dark matter density. Statistical properties of the transmitted flux can constrain the amplitude and shape of the matter power spectrum at high redshift, test the assumption of Gaussian initial conditions, and probe the evolution of dark energy by measuring the Hubble parameter H(z). Simulations predict increased Lya absorption in the vicinity of galaxies, but observations show a Lya deficit within Delta_r ~ 0.5 Mpc/h (comoving). We investigate idealized models of "winds" and find that they must eliminate neutral hydrogen out to comoving radii ~1.5 Mpc/h to marginally explain the data. Winds of this magnitude suppress the flux power spectrum by \~0.1 dex but have little effect on the distribution function or threshold crossing frequency. In light of the stringent demands on winds, we consider the alternative possibility that extended Lya emission from target galaxies replaces absorbed flux, but we conclude that this explanation is unlikely. Taking full advantage of the data coming from large telescopes and from the Sloan Digital Sky Survey will require more complete understanding of the galaxy proximity effect, careful attention to continuum determination, and more accurate numerical predictions, with the goal of reaching 5-10% precision on key cosmological quantities.
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astro-ph.CO 2years
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Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
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Exploring the Cosmic Dawn through the 21 cm Forest and High-redshift Radio Sources with the SKA
Review of 21 cm forest observations as a probe of the epoch of reionization and fundamental physics using the Square Kilometre Array.
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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.