Revealing the z~2.5 Cosmic Web With 3D Lyman-Alpha Forest Tomography: A Deformation Tensor Approach
Khee-Gan Lee, Martin White

TL;DR
This paper demonstrates that 3D Lyman-alpha forest tomography can accurately classify the cosmic web at z~2.5, providing a powerful tool for studying large-scale structure during a key epoch in galaxy formation.
Contribution
It introduces a deformation tensor approach to classify cosmic web structures from Lyman-alpha forest maps, achieving high accuracy comparable to galaxy-based methods at low redshift.
Findings
70% volume correctly classified relative to dark matter web
99% classification within 1 eigenvalue accuracy
Survey geometry impacts cosmic web recovery unless sufficiently large
Abstract
Studies of cosmological objects should take into account their positions within the cosmic web of large-scale structure. Unfortunately, the cosmic web has only been extensively mapped at low-redshifts (), using galaxy redshifts as tracers of the underlying density field. At , the required galaxy densities are inaccessible for the foreseeable future, but 3D reconstructions of Lyman- forest absorption in closely-separated background QSOs and star-forming galaxies already offer a detailed window into large-scale structure. We quantify the utility of such maps for studying the cosmic web by using realistic Ly forest simulations matched to observational properties of upcoming surveys. A deformation tensor-based analysis is used to classify voids, sheets, filaments and nodes in the flux, which is compared to those determined from the underlying…
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