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Generating mock data sets for large-scale Lyman-{\alpha} forest correlation measurements
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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.
Forward citations
Cited by 2 Pith papers
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Playground of Lognormal Seminumerical Simulations of~the~Lyman~$\alpha$ Forest: Thermal History of the Intergalactic Medium
A lognormal seminumerical simulator of the Lyman-alpha forest, fit to observed flux power spectra, returns estimates of the intergalactic temperature, temperature-density slope, and Jeans length at z=3 to 5.
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Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest
Review of machine learning applications for analyzing Lyman-alpha forest observations to probe cosmology, reionization, and dark matter.
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