LyMAS reloaded: improving the predictions of the large-scale Lyman-{\alpha} forest statistics from dark matter density and velocity fields

TL;DR

LyMAS2 enhances predictions of large-scale Lyman-alpha forest clustering by calibrating from hydrodynamical simulations and applying Wiener filtering to dark matter fields, achieving high accuracy in mock spectra for cosmological studies.

Contribution

This work introduces LyMAS2, an improved method that combines dark matter density and velocity information to better predict Lyman-alpha forest statistics from moderate resolution simulations.

Findings

Achieves ~5% accuracy in 2-point correlation functions

Reproduces flux 1d power spectrum within ~2%

Generates large mock spectra for BOSS survey analysis

Abstract

We present LyMAS2, an improved version of the "Lyman-{\alpha} Mass Association Scheme" aiming at predicting the large-scale 3d clustering statistics of the Lyman-{\alpha} forest (Ly-{\alpha}) from moderate resolution simulations of the dark matter (DM) distribution, with prior calibrations from high resolution hydrodynamical simulations of smaller volumes. In this study, calibrations are derived from the Horizon-AGN suite simulations, (100 Mpc/h)^3 comoving volume, using Wiener filtering, combining information from dark matter density and velocity fields (i.e. velocity dispersion, vorticity, line of sight 1d-divergence and 3d-divergence). All new predictions have been done at z=2.5 in redshift-space, while considering the spectral resolution of the SDSS-III BOSS Survey and different dark matter smoothing (0.3, 0.5 and 1.0 Mpc/h comoving). We have tried different combinations of dark matter fields and found that LyMAS2, applied to the Horizon-noAGN dark matter fields, significantly improves the predictions of the Ly-{\alpha} 3d clustering statistics, especially when the DM overdensity is associated with the velocity dispersion or the vorticity fields. Compared to the hydrodynamical simulation trends, the 2-point correlation functions of pseudo-spectra generated with LyMAS2 can be recovered with relative differences of ~5% even for high angles, the flux 1d power spectrum (along the light of sight) with ~2% and the flux 1d probability distribution function exactly. Finally, we have produced several large mock BOSS spectra (1.0 and 1.5 Gpc/h) expected to lead to much more reliable and accurate theoretical predictions.