Constraints on warm dark matter from UV luminosity functions of high-z galaxies with Bayesian model comparison

TL;DR

This study uses Bayesian analysis of high-redshift galaxy UV luminosity functions to place constraints on warm dark matter particle mass, finding masses below 2 keV are unlikely, with future JWST data expected to tighten these bounds.

Contribution

It introduces a flexible astrophysical model combined with Bayesian inference to constrain warm dark matter properties using UV luminosity functions.

Findings

WDM particle masses below 2 keV are rejected at 95% credibility.

UV LFs only weakly favor CDM over WDM with current data.

Future JWST observations could raise the lower bound to ~2.5 keV.

Abstract

The number density of small dark matter (DM) halos hosting faint high-redshift galaxies is sensitive to the DM free-streaming properties. However, constraining these DM properties is complicated by degeneracies with the uncertain baryonic physics governing star formation. In this work, we use a flexible astrophysical model and a Bayesian inference framework to analyse ultra-violet (UV) luminosity functions (LFs) at z=6-8. We vary the complexity of the galaxy model (single vs double power law for the stellar -- halo mass relation) as well as the matter power spectrum (cold DM vs thermal relic warm DM), comparing their Bayesian evidences. Adopting a conservatively wide prior range for the WDM particle mass, we show that the UV LFs at z=6-8 only weakly favour CDM over WDM. We find that particle masses of $\lesssim$2 keV are rejected at a 95% credible level in all models that have a WDM-like power spectrum cutoff. This bound should increase to ~2.5 keV with the James Webb Space Telescope (JWST).