A Statistical Semi-Empirical Model: Satellite galaxies in Groups and Clusters

We present STEEL a STatistical sEmi-Empirical modeL designed to probe the distribution of satellite galaxies in groups and clusters. Our fast statistical methodology relies on tracing the abundances of central and satellite haloes via their mass functions at all cosmic epochs with virtually no limitation on cosmic volume and mass resolution. From mean halo accretion histories and subhalo mass functions the satellite mass function is progressively built in time via abundance matching techniques constrained by number densities of centrals in the local Universe. By enforcing dynamical merging timescales as predicted by high-resolution N-body simulations, we obtain satellite distributions as a function of stellar mass and halo mass consistent with current data. We show that stellar stripping, star formation, and quenching play all a secondary role in setting the number densities of massive satellites above $M_*\gtrsim 3\times 10^{10}\, M_{\odot}$. We further show that observed star formation rates used in our empirical model over predict low-mass satellites below $M_*\lesssim 3\times 10^{10}\, M_{\odot}$, whereas, star formation rates derived from a continuity equation approach yield the correct abundances similar to previous results for centrals.Comment: 21 pages, 17 Figures. MNRAS, in pres

Predicting fully self-consistent satellite richness, galaxy growth and starformation rates from the STastical sEmi-Empirical modeL steel

Observational systematics complicate comparisons with theoretical models limiting understanding of galaxy evolution. In particular, different empirical determinations of the stellar mass function imply distinct mappings between the galaxy and halo masses, leading to diverse galaxy evolutionary tracks. Using our state-of-the-art STatistical sEmi-Empirical modeL, STEEL, we show fully self-consistent models capable of generating galaxy growth histories that simultaneously and closely agree with the latest data on satellite richness and star formation rates at multiple redshifts and environments. Central galaxy histories are generated using the central halo mass tracks from state-of-the-art statistical dark matter accretion histories coupled to abundance matching routines. We show that too flat high-mass slopes in the input stellar mass–halo mass relations as predicted by previous works, imply non-physical stellar mass growth histories weaker than those implied by satellite accretion alone. Our best-fitting models reproduce the satellite distributions at the largest masses and highest redshifts probed, the latest data on star formation rates and its bimodality in the local Universe, and the correct fraction of ellipticals. Our results are important to predict robust and self-consistent stellar mass–halo mass relations and to generate reliable galaxy mock catalogues for the next generations of extragalactic surveys such as Euclid and LSST