Mapping the Three-dimensional Lyα Forest Large-scale Structure in Real and Redshift Space
This work presents a new physically motivated supervised machine-learning method, HYDRO-BAM, to reproduce the three-dimensional Lyα forest field in real and redshift space, which learns from a reference hydrodynamic simulation and thereby saves about seven orders of magnitude in computing time. We show that our method is accurate up to k ~ 1 h Mpc
Sinigaglia, Francesco et al.
Fecha de publicación:
3
2022