Assessing the Predictive Power of Galaxy Formation Models: A Comparison of Predicted and Observed Rest-Frame Optical Luminosity Functions at 2.0<z<3.3
Danilo Marchesini, Pieter van Dokkum (Yale University)

TL;DR
This study evaluates how well current galaxy formation models predict the rest-frame optical luminosity functions of galaxies at redshifts 2.0 to 3.3, revealing successes and notable discrepancies with observations.
Contribution
It compares predictions of semianalytic and hydrodynamic galaxy formation models to observed luminosity functions at high redshift, highlighting areas of agreement and failure.
Findings
Models match observations at some luminosities and redshifts.
All models predict increasing luminosity density over time, contrary to observations.
Discrepancies in galaxy color evolution suggest incomplete modeling of galaxy formation.
Abstract
Recent galaxy formation models successfully reproduce the local luminosity function (LF) of galaxies by invoking mechanisms to suppress star formation in low- and high-mass galaxies. As these models are optimized to fit the LF at low redshift, a crucial question is how well they predict the LF at earlier times. Here we compare recently measured rest-frame V-band LFs of galaxies at redshifts 2.0<z<3.3 to predictions of semianalytic models by De Lucia & Blaizot and Bower et al. and hydrodynamic simulations by Dave et al.. The models succeed for some luminosity and redshift ranges and fail for others. A notable success is that the Bower et al. model provides a good match to the observed LF at z~3. However, all models predict an increase with time of the rest-frame V-band luminosity density, whereas the observations show a decrease. The models also have difficulty matching the observed…
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.
