2019/01/31 by David Valcin, Francisco Villaescusa-Navarro, Licia Verde +1 · 17 citations
Physics and Astronomy · #Cosmology and Gravitation Theories #Dark Matter and Cosmic Phenomena #Dark matter #Galaxies: Formation, Evolution, Phenomena #Halo #Halo effect #Markov chain Monte Carlo #Massless particle #Matter power spectrum #Monte Carlo method #Neutrino #Redshift #Spectral density #astro-ph.CO
paper · pdf · doi:10.1088/1475-7516/2019/12/057
published in Journal of Cosmology and Astroparticle Physics 2019(12), 057 (Institute of Physics) · 23 pages, (33 with references and appendices), 14 figures. Changes to match accepted version by JCAP
openalex created_date 2019/01/25 · arxiv created 2019/10/25 · openalex publication_date 2019/12/18 · arxiv updated 2020/01/08 · openalex updated_date 2026/08/05
We study the clustering properties of dark matter haloes in real- and redshift-space in cosmologies with massless and massive neutrinos through a large set of state-of-the-art N-body simulations. We provide quick and easy-to-use prescriptions for the halo bias on linear and mildly non-linear scales, both in real and redshift-space, which are valid also for massive neutrinos cosmologies. Finally we present a halo bias emulator, BE-HaPPY , calibrated on the N-body simulations, which is fast enough to be used in the standard Markov Chain Monte Carlo approach to cosmological inference. For a fiducial standard ΛCDM cosmology BE-HaPPY reproduces the simulation inputs with percent or sub-percent accuracy for the halo mass cuts it is calibrated on (M>5 × 10 11 , 10 12 , 3 × 10 12 , 10 13 h -1 M ⊙ ) on the scales of interest (linear and well into the mildly non-linear regime). The approach presented here represents a well defined route to meeting the halo-bias accuracy requirements for the analysis of next-generation large-scale structure surveys. The software BE-HaPPY can run both in emulator mode and in calibration mode, on user-supplied simulations outputs, and is made publicly available.