Observational Requirements for Lyman-alpha Forest Tomographic Mapping of Large-Scale Structure at z ~ 2

TL;DR

This paper assesses the observational requirements, such as sightline density and exposure time, necessary to create 3D maps of large-scale structure at z ~ 2 using the Lyman-alpha forest, enabling efficient high-redshift universe studies.

Contribution

It provides detailed simulations and estimates of observational parameters needed for Lyman-alpha forest tomography at high redshift, guiding future large-scale structure mapping efforts.

Findings

Spectra with S/N = 4 per angstrom can trace dark matter overdensities.

Exposure times of 4-10 hours are sufficient for desired spatial resolutions.

Surveying 1 deg^2 covers a volume of ~10^6 h^{-3} Mpc^3 at z=2.3.

Abstract

The z > 2 Lyman-alpha (Lya) forest traces the underlying dark-matter distribution on large scales and, given sufficient sightlines, can be used to create 3D maps of large-scale structure. We examine the observational requirements to construct such maps and estimate the signal-to-noise as a function of exposure time and sightline density. Sightline densities at z = 2.25 are n_los = [360, 1200,3300] deg^{-2} at limiting magnitudes of g =[24.0, 24.5,25.0], resulting in transverse sightline separations of d_perp = [3.6, 1.9, 1.2] h^{-1} Mpc, which roughly sets the reconstruction scale. We simulate these reconstructions using mock spectra with realistic noise properties, and find that spectra with S/N = 4 per angstrom can be used to generate maps that clearly trace the underlying dark-matter at overdensities of rho/<rho> ~ 1. For the VLT/VIMOS spectrograph, exposure times t_exp = [4, 6, 10] hrs are sufficient for maps with spatial resolution epsilon_3d = [5.0, 3.2, 2.3] h^{-1} Mpc. Assuming ~ 250 h^{-1} Mpc is probed along the line-of-sight, 1 deg^2 of survey area would cover a comoving volume of ~ 10^6 h^{-3} Mpc^3 at <z>=2.3, enabling efficient mapping of large volumes with 8-10m telescopes. These maps could be used to study galaxy environments, detect proto-clusters, and study the topology of large-scale structure at high-z.