Semi-analytic galaxies – I. Synthesis of environmental and star-forming regulation mechanisms

Abstract

We present results from the semi-analytic model of galaxy formation sag applied on the MultiDark simulation MDPL2. sag features an updated supernova (SN) feedback scheme and a robust modelling of the environmental effects on satellite galaxies. This incorporates a gradual starvation of the hot gas halo driven by the action of ram pressure stripping (RPS), that can affect the cold gas disc, and tidal stripping (TS), which can act on all baryonic components. Galaxy orbits of orphan satellites are integrated providing adequate positions and velocities for the estimation of RPS and TS. The star formation history and stellar mass assembly of galaxies are sensitive to the redshift dependence implemented in the SN feedback model. We discuss a variant of our model that allows to reconcile the predicted star formation rate density at z 3 with the observed one, at the expense of an excess in the faint end of the stellar mass function at z = 2. The fractions of passive galaxies as a function of stellar mass, halo mass and the halo-centric distances are consistent with observational measurements. The model also reproduces the evolution of the main sequence of star forming central and satellite galaxies. The similarity between them is a result of the gradual starvation of the hot gas halo suffered by satellites, in which RPS plays a dominant role. RPS of the cold gas does not affect the fraction of quenched satellites but it contributes to reach the right atomic hydrogen gas content for more massive satellites (M 10 10 M ).

Exploring the high-mass end of the stellar mass function of star-forming galaxies at cosmic noon

“…With this in mind, Knebe et al (2018) applied three SAMs to the dark matter halos and merger trees from MDPL2. The three SAMs, GALACTICUS (Benson 2012), SAG (Cora et al 2018), and SAGE (Croton et al 2016(Croton et al ) differ in their et al (2007, who showed a factor of 100 difference between massive galaxy number densities from the Millennium Run SAM (De Lucia et al 2006) and observations in the Palomar/DEEP2 survey (e.g., Davis et al 2003, Giavalisco et al 2004, Bundy et al 2005, Davis et al 2007) at z ∼ 2.…”

“…Bolshoi-Planck and MDPL2 MDPL2-SAG MDPL2-GALACTICUS MDPL2-SAGE 3 < z < 3.5 Figure 10. Comparison of the empirical galaxy stellar mass function for 1.5 < z < 3.5 star-forming galaxies in the SHELA footprint to the stellar mass functions from three classes of theoretical models: hydrodynamical models from IllustrisTNG using rTNG300 (Pillepich et al 2018b), abundance matching models from the UniverseMachine (Behroozi et al 2019) populating dark matter halos from Bolshoi-Planck, and three different semi-analytic models (SAMs), namely SAG (radio-mode AGN feedback, Cora et al 2018), GALACTICUS (radio-mode AGN feedback, Benson 2012), and SAGE (quasar-mode AGN feedback, Croton et al 2016) applied to the MDPL2 dark matter simulation. In our lowest redshift bin (1.5 < z < 2) results from all three model classes are in rough agreement with results from the SHELA footprint.…”

“…Multi-DarkPlanck2 and Bolshoi-Planck dark-matteronly simulations (e.g., Klypin et al 2016, Rodríguez-Puebla et al 2016, Knebe et al 2018) simulate much larger volumes of 0.25h −1 Gpc and 1.0 h −1 Gpc, respectively, on a side with different resolutions. The properties they output for the dark-matter component can be combined with different implementations of baryonic physics in SAMs (e.g., Benson 2012, Somerville & Davé 2015, Croton et al 2016, Cora et al 2018 or in abundance matching models (e.g., Behroozi et al 2010, Behroozi et al 2019 to model galaxy evolution.…”

The atomic hydrogen content of the post-reionization Universe

“…The most recent renditions of several independent SAMs have included prescriptions to partition the cold gas in its atomic and molecular components, based either on empirical relations or on results from sophisticated numerical simulations (e.g. Fu et al 2010;Lagos et al 2011;Kim et al 2011;Somerville & Davé 2015;Stevens et al 2017;Xie et al 2017;Zoldan et al 2017;Cora et al 2018). These models can provide reliable mock 21 cm maps, thereby helping to understand the relevant processes determining the observed 21 cm signal.…”

Compact groups from semi-analytical models of galaxy formation – I. A comparative study of frequency and nature

“…Elliptical galaxies: M bulge /M * ≥ E lim , Spiral galaxies: S lim < M bulge /M * < E lim , and Irregular galaxies: M bulge /M * ≤ S lim , We adopted limiting values E lim and S lim to obtain the best recovery of the observational data: S lim = 0.03 and E lim = 0.7 for DLB b , G11 b , G13 b , GII b and HrII b s (Guo et al 2011), S lim = 0 and E lim = 0.7 for HrI b (Bertone et al 2007), while S lim = 0 and E lim = 0.85 for SAG b (Cora et al 2018). The MS SAMs reproduce fairly similar morphological mixes as observed.…”