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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