Field-level Lyman-alpha forest modelling in redshift space via augmented non-local Fluctuating Gunn-Peterson Approximation

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Main Authors: Sinigaglia, Francesco, Kitaura, Francisco-Shu, Nagamine, Kentaro, Oku, Yuri, Balaguera-Antolínez, Andrés
Format: Preprint
Published: 2023
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author Sinigaglia, Francesco
Kitaura, Francisco-Shu
Nagamine, Kentaro
Oku, Yuri
Balaguera-Antolínez, Andrés
author_facet Sinigaglia, Francesco
Kitaura, Francisco-Shu
Nagamine, Kentaro
Oku, Yuri
Balaguera-Antolínez, Andrés
contents We present an improved analytical model to predict the Lyman-alpha forest at the field level in redshift space from the dark matter field, expanding upon the widely-used Fluctuating Gunn-Peterson approximation (FGPA). In particular, we introduce the dependence on the cosmic web environment (knots, filaments, sheets, voids) in the model, thereby effectively accounting for non-local bias. Furthermore, we include a detailed treatment of velocity bias in the redshift space distortions modelling, allowing the velocity bias to be cosmic-web dependent. We find evidence for a significant difference of the same model parameters in different environments, suggesting that for the investigated setup the simple standard FGPA is not able to adequately predict the Lyman-alpha forest in the different cosmic web regimes. We reproduce the summary statistics of the reference cosmological hydrodynamic simulation we use for comparison, yielding accurate mean transmitted flux, probability distribution function, 3D power spectrum, and bispectrum. In particular, we achieve maximum deviation and average deviations accuracy in the Lyman-alpha forest 3D power spectrum of $\sim 3\%$ and $\sim 0.1\%$ up to $k\sim 0.4 \, h \, {\rm Mpc}^{-1}$, $\sim 5\%$ and $\sim 1.8\%$ up to $k \sim 1.4 \, h \, {\rm Mpc}^{-1}$. Our new model outperforms previous analytical efforts to predict the Lyman-alpha forest at the field level in all the probed summary statistics, and has the potential to become instrumental in the generation of fast accurate mocks for covariance matrices estimation in the context of current and forthcoming Lyman-alpha forest surveys.
format Preprint
id arxiv_https___arxiv_org_abs_2305_10428
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Field-level Lyman-alpha forest modelling in redshift space via augmented non-local Fluctuating Gunn-Peterson Approximation
Sinigaglia, Francesco
Kitaura, Francisco-Shu
Nagamine, Kentaro
Oku, Yuri
Balaguera-Antolínez, Andrés
Cosmology and Nongalactic Astrophysics
Astrophysics of Galaxies
We present an improved analytical model to predict the Lyman-alpha forest at the field level in redshift space from the dark matter field, expanding upon the widely-used Fluctuating Gunn-Peterson approximation (FGPA). In particular, we introduce the dependence on the cosmic web environment (knots, filaments, sheets, voids) in the model, thereby effectively accounting for non-local bias. Furthermore, we include a detailed treatment of velocity bias in the redshift space distortions modelling, allowing the velocity bias to be cosmic-web dependent. We find evidence for a significant difference of the same model parameters in different environments, suggesting that for the investigated setup the simple standard FGPA is not able to adequately predict the Lyman-alpha forest in the different cosmic web regimes. We reproduce the summary statistics of the reference cosmological hydrodynamic simulation we use for comparison, yielding accurate mean transmitted flux, probability distribution function, 3D power spectrum, and bispectrum. In particular, we achieve maximum deviation and average deviations accuracy in the Lyman-alpha forest 3D power spectrum of $\sim 3\%$ and $\sim 0.1\%$ up to $k\sim 0.4 \, h \, {\rm Mpc}^{-1}$, $\sim 5\%$ and $\sim 1.8\%$ up to $k \sim 1.4 \, h \, {\rm Mpc}^{-1}$. Our new model outperforms previous analytical efforts to predict the Lyman-alpha forest at the field level in all the probed summary statistics, and has the potential to become instrumental in the generation of fast accurate mocks for covariance matrices estimation in the context of current and forthcoming Lyman-alpha forest surveys.
title Field-level Lyman-alpha forest modelling in redshift space via augmented non-local Fluctuating Gunn-Peterson Approximation
topic Cosmology and Nongalactic Astrophysics
Astrophysics of Galaxies
url https://arxiv.org/abs/2305.10428