Generating mock data sets for large-scale Lyman-{\alpha} forest correlation measurements

TL;DR

This paper introduces an efficient method for generating mock Lyman-alpha forest data sets, enabling accurate modeling of large-scale structure measurements and systematic effects in high-redshift quasar surveys.

Contribution

The paper presents a novel, computationally efficient approach to produce mock Lyman-alpha forest data focusing on lines of sight, calibrated to match key statistical properties of the flux.

Findings

Method accurately reproduces power spectrum and flux distribution

Enables modeling of survey systematic effects

Predicts measurement errors for BOSS-like surveys

Abstract

Massive spectroscopic surveys of high-redshift quasars yield large numbers of correlated Lyman {\alpha} absorption spectra that can be used to measure large-scale structure. Simulations of these surveys are required to accurately interpret the measurements of correlations and correct for systematic errors. An efficient method to generate mock realizations of Lyman {\alpha} forest surveys is presented which generates a field over the lines of sight to the survey sources only, instead of having to generate it over the entire three-dimensional volume of the survey. The method can be calibrated to reproduce the power spectrum and one-point distribution function of the transmitted flux fraction, as well as the redshift evolution of these quantities, and is easily used for modeling any survey systematic effects. We present an example of how these mock surveys are applied to predict the measurement errors in a survey with similar parameters as the BOSS quasar survey in SDSS-III.