Stochastic star formation activity of galaxies within the first billion years probed by JWST

TL;DR

This study uses JWST data and a stochastic star formation history model to analyze the burstiness of high-redshift galaxies, revealing how star formation variability influences galaxy properties and the UV luminosity function.

Contribution

Introduces a stochastic SFH model in CIGALE to better characterize burstiness in early galaxies and links star formation variability to galaxy evolution at high redshift.

Findings

High stochasticity models better fit z>6 galaxy SEDs.

Burstiness fraction increases with redshift for massive galaxies.

Less than 20% of low-mass galaxies are bursty, with uncertain estimates.

Abstract

In this work, we aim at characterizing the burstiness level of high-redshift galaxy SFHs and its evolution. We implement a stochastic SFH in CIGALE using PSD, to estimate the burstiness level of star formation in galaxies at 6<z<12. We find that SFHs with a high level of stochasticity better reproduce the SEDs of z>6 galaxies, while smoother assumptions introduce biases when applied to galaxies with bursty star-formation activity. The assumed stochasticity level of the SFH also affects the constraints on galaxies' physical properties, including the main sequence. Successively assuming different levels of burstiness, we determined the best-suited SFH for each 6<z<12 galaxy in the JADES sample from a Bayes Factor analysis. Galaxies are classified according to their level of burstiness, and the corresponding physical properties are associated to them. For massive galaxies (8.8< logM*/Msun<9.5), the fraction of bursty galaxies increases from 0.38+/-0.08 to 0.77+/-0.2 at z~6 and z~12, respectively. At all redshifts, only <20% of low-mass galaxies are classified as bursty; although, this estimate is uncertain because their faintness leads to a low S/N. For bursty galaxies, the log10(SFR10/SFR100) ratio, another indicator of bursty star formation, does not evolve with redshift, but the fraction of galaxies with a high log10(SFR10/SFR100) slightly increases from 0.28+/-0.06 to 0.38+/-0.11 between z~6 and z~9. We include additional constraints from observations on sigmaUV, the dispersion of the UV magnitude distribution, and SFE, finding a maximum of 0.72+/-0.02 mag and 0.06+/-0.01 for sigmaUV and SFE, respectively. This confirms that neither alone is responsible for the weak evolution of the UVLF at z>10. Our results add further evidence that a combination with other mechanisms is likely responsible for the high-z UVLF. The stochastic SFH module is public as part of CIGALE version 2025.1.