A physically-motivated template set for high-z galaxy SED fitting

TL;DR

This paper presents a new physically-motivated spectral template set for fitting high-redshift galaxy SEDs, calibrated with galaxy formation models and tested on JWST data, revealing bursty star formation and early stellar assembly.

Contribution

The authors develop and validate a novel SED-fitting template set specifically designed for high-z galaxies, incorporating bursty star formation and enabling detailed property inference.

Findings

High-z galaxies often exhibit bursty star formation.

Galaxies at z > 8 follow a star-forming main sequence with higher normalization.

Galaxies form stars earlier than some models predict.

Abstract

We introduce a new physically-motivated spectral template set for fitting the spectral energy distributions (SEDs) of high-z galaxies. We use the public galaxy formation code ARES to generate star formation histories of thirteen representative galaxies with diverse masses and generate their predicted spectra across a set of redshifts at z > 6. The model parameters are calibrated to reproduce the properties of z > 6 galaxies observed by HST. Motivated by the apparent importance of bursty star formation at high redshifts, we also include templates with recent starbursts. We use these templates with the SED-fitting code EAZY to analyze both an independent theoretical model and a public sample of JWST-observed galaxies from the JADES survey. The comparison with a semi-analytic model demonstrates that our fitting framework accurately measures the galaxy properties, even when the underlying assumptions of the model differ from ours. Our preliminary application to JWST data shows that galaxies at z > 8 are often bursty (especially at small galaxy masses), follow a star-forming main sequence similar to those at lower redshift (albeit with a higher normalization), and form stars earlier than expected in ares. Our SED-fitting framework is very fast (thanks to the efficiency of EAZY) but provides full inferred star formation histories for each source. Additionally, it enables a direct comparison to theoretical models and helps point toward improvements necessary in those models.