IAFE   05512
INSTITUTO DE ASTRONOMIA Y FISICA DEL ESPACIO
Unidad Ejecutora - UE
artículos
Título:
Baryon effects on void statistics in the EAGLE simulation
Autor/es:
LAGOS, CLAUDIA D. P.; PAILLAS, ENRIQUE; HELLY, JOHN; TISSERA, PATRICIA; PADILLA, NELSON; SCHALLER, MATTHIEU
Revista:
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Editorial:
WILEY-BLACKWELL PUBLISHING, INC
Referencias:
Año: 2017 vol. 470 p. 4434 - 4452
ISSN:
0035-8711
Resumen:
Cosmic voids are promising tools for cosmological tests due to their sensitivity to dark energy, modified gravity and alternative cosmological scenarios. Most previous studies in the literature of void properties use cosmological N-body simulations of dark matter (DM) particles that ignore the potential effect of baryonic physics. Using a spherical underdensity finder, we analyse voids using the mass field and subhalo tracers in the Evolution and Assembly of Galaxies and their Environment (EAGLE) simulations, which follow the evolution of galaxies in a Λ cold dark matter universe with state-of-the-art subgrid models for baryonic processes in a (100 cMpc)3 volume. We study the effect of baryons on void statistics by comparing results with DM-only simulations that use the same initial conditions as EAGLE. When identifying voids in the mass field, we find that a DM-only simulation produces 24 per cent more voids than a hydrodynamical one due to the action of galaxy feedback polluting void regions with hot gas, specially for small voids with rvoid ≤ 10 Mpc. We find that the way in which galaxy tracers are selected has a strong impact on the inferred void properties. Voids identified using galaxies selected by their stellar mass are larger and have cuspier density profiles than those identified by galaxies selected by their total mass. Overall, baryons have minimal effects on void statistics, as void properties are well captured by DM-only simulations, but it is important to account for how galaxies populate DM haloes to estimate the observational effect of different cosmological models on the statistics of voids.