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Title: Towards physics responsible for large-scale Lyman-α forest bias parameters

Journal Article · · Journal of Cosmology and Astroparticle Physics
 [1]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States)

Using a series of carefully constructed numerical experiments based on hydrodynamic cosmological SPH simulations, we attempt to build an intuition for the relevant physics behind the large scale density (bδ) and velocity gradient (bη) biases of the Lyman-α forest. Starting with the fluctuating Gunn-Peterson approximation applied to the smoothed total density field in real-space, and progressing through redshift-space with no thermal broadening, redshift-space with thermal broadening and hydrodynamically simulated baryon fields, we investigate how approximations found in the literature fare. We find that Seljak's 2012 analytical formulae for these bias parameters work surprisingly well in the limit of no thermal broadening and linear redshift-space distortions. We also show that his bη formula is exact in the limit of no thermal broadening. Since introduction of thermal broadening significantly affects its value, we speculate that a combination of large-scale measurements of bη and the small scale flux PDF might be a sensitive probe of the thermal state of the IGM. Lastly, we find that large-scale biases derived from the smoothed total matter field are within 10–20% to those based on hydrodynamical quantities, in line with other measurements in the literature.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP)
Grant/Contract Number:
SC00112704
OSTI ID:
1246806
Report Number(s):
BNL-111995-2016-JA; KA2301020
Journal Information:
Journal of Cosmology and Astroparticle Physics, Vol. 2016, Issue 03; ISSN 1475-7516
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 16 works
Citation information provided by
Web of Science

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Cited By (5)

Scale-dependent bias and bispectrum in neutrino separate universe simulations journal June 2018
Measurement of Void Bias Using Separate Universe Simulations journal January 2020
Scale-dependent bias and bispectrum in neutrino separate universe simulations text January 2017
The Lyman-α power spectrum—CMB lensing convergence cross-correlation journal January 2018
The cross-correlation between 21cm intensity mapping maps and the Lyman-alpha forest in the post-reionization era text January 2016

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