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

TL;DR

This paper introduces STEEL, a semi-empirical model that accurately predicts galaxy growth, satellite richness, and star formation rates across different environments and redshifts, aiding future galaxy survey analyses.

Contribution

The paper presents STEEL, a novel self-consistent semi-empirical model that aligns galaxy evolution predictions with diverse observational data, improving upon previous models.

Findings

Reproduces satellite distributions at high masses and redshifts.

Matches observed star formation rates and their bi-modality.

Accurately predicts the fraction of elliptical galaxies.

Abstract

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-fit models reproduce the satellite distributions at the largest masses and highest redshifts probed, the latest data on star formation rates and its bi-modality 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 extra-galactic surveys such as Euclid and LSST.