Shedding light on the star formation rate-halo accretion rate connection and halo quenching mechanism via DECODE, the Discrete statistical sEmi-empiriCal mODEl

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 <ns0:sc>DECODE</ns0:sc> (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 the SFR and HAR allows us 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 stellar mass-halo mass relation (or SMF); and (3) to align with the observed steep (flat) low-mass end of the stellar mass-halo mass (or SMF) additional quenching processes in the least massive haloes are needed. Conclusions. <ns0:sc>DECODE</ns0:sc> 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.