Kavli Affiliate: Yingjie Peng
| First 5 Authors: Hao Fu, Lumen Boco, Francesco Shankar, Andrea Lapi, Mohammadreza Ayromlou
| Summary:
Aims: The relative roles of the physical mechanisms involved in quenching
galaxy star formation are still unclear. We tackle this fundamental problem
with our cosmological semi-empirical model DECODE (Discrete statistical
sEmi-empiriCal mODEl), designed to predict galaxy stellar mass assembly
histories, from minimal input assumptions. Methods: Specifically, in this work
the star formation history of each galaxy is calculated along its progenitor
dark matter halo by assigning at each redshift a star formation rate extracted
from a monotonic star formation rate-halo accretion rate (SFR-HAR) relation
derived from abundance matching between the (observed) SFR function and the
(numerically predicted) HAR function, a relation that is also predicted by the
TNG100 simulation. SFRs are integrated across cosmic time to build up the mass
of galaxies, which may halt their star formation following input physical
quenching recipes. Results: In this work we test the popular halo quenching
scenario and we find that: 1) the assumption of a monotonic relation between
SFR and HAR allows to reproduce the number densities of the bulk of
star-forming galaxies in the local Universe; 2) the halo quenching is
sufficient to reproduce the statistics of the quenched galaxies and flat
(steep) high-mass end of the SMHM relation (SMF); and 3) to align with the
observed steep (flat) low-mass end of the SMHM (SMF) additional quenching
processes in the least massive haloes are needed. Conclusions: DECODE is an
invaluable tool and will pave the way to investigate the origin of newly
observed high-redshift objects from the latest ongoing facilities such as JWST
and Euclid.
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