Confronting theoretical models with the observed evolution of the galaxy population out to z=4
Bruno Henriques (MPA-Garching), Simon White (MPA-Garching), Gerard, Lemson (MPA-Garching), Peter Thomas (Sussex), Qi Guo (NAOC, Durham),, Gabriel-Dominique Marleau (MPA-Garching, Montereal), Roderik Overzier, (MPA-Garching)

TL;DR
This study compares semi-analytic galaxy formation models with high-redshift observations, revealing strengths and limitations in reproducing galaxy counts, redshift distributions, and luminosity functions up to z=4, and highlighting the impact of stellar population synthesis choices.
Contribution
It provides a detailed comparison between galaxy formation models and observations, emphasizing the effects of different stellar population synthesis codes on predicted galaxy properties.
Findings
Models reproduce B, i, J counts well but overpredict at longer wavelengths.
Including TP-AGB emission improves high-redshift galaxy predictions.
Luminosity functions match observations up to z~3, with discrepancies at lower luminosities.
Abstract
[abridged] We construct lightcones for the semi-analytic galaxy formation simulation of Guo et al. (2011) and make mock catalogues for comparison with deep high-redshift surveys. Photometric properties are calculated with two different stellar population synthesis codes (Bruzual & Charlot 2003; Maraston 2005) in order to study sensitivity to this aspect of the modelling. The catalogues are publicly available and include photometry for a large number of observed bands from 4000{\deg}A to 6{\mu}m, as well as rest-frame photometry and intrinsic properties of the galaxies. Guo et al. (2011) tuned their model to fit the low-redshift galaxy population but noted that at z > 1 it overpredicts the abundance of galaxies below the "knee" of the stellar mass function. Here we extend the comparison to deep galaxy counts in the B, i, J, K and IRAC 3.6{\mu}m, 4.5{\mu}m and 5.8{\mu}m bands, to the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
