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Title: Observational requirements for Lyα forest tomographic mapping of large-scale structure at z ∼ 2

Journal Article · · Astrophysical Journal
;  [1];  [2]; ;  [3]
  1. Max Planck Institute for Astronomy, Königstuhl 17, D-69117 Heidelberg (Germany)
  2. E.O. Lawrence Berkeley National Lab, 1 Cyclotron Rd., Berkeley, CA 94720 (United States)
  3. Department of Physics, Carnegie-Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States)

The z ≳ 2 Lyα forest traces the underlying dark matter distribution on large scales and, given sufficient sightlines, can be used to create three-dimensional (3D) maps of large-scale structures. 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 {sub los} ≈ [360, 1200, 3300] deg{sup –2} at limiting magnitudes of g = [24.0, 24.5, 25.0], resulting in transverse sightline separations of (d ) ≈ [3.6, 1.9, 1.2] h {sup –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 ρ/(ρ) ∼ 1. For the VLT/VIMOS spectrograph, exposure times t {sub exp} = [4, 6, 10] hr are sufficient for maps with spatial resolution ε{sub 3D} = [5.0, 3.2, 2.3] h {sup –1} Mpc. Assuming ∼250 h {sup –1} Mpc is probed along the line of sight, 1 deg{sup 2} of survey area would cover a comoving volume of ≈10{sup 6} h {sup –3} Mpc{sup 3} at (z) ∼ 2.3, enabling the efficient mapping of large volumes with 8-10 m telescopes. These maps could be used to study galaxy environments, the topology of large-scale structures at high z, and to detect proto-clusters.

OSTI ID:
22356664
Journal Information:
Astrophysical Journal, Vol. 788, Issue 1; Other Information: Country of input: International Atomic Energy Agency (IAEA); ISSN 0004-637X
Country of Publication:
United States
Language:
English