Julien Devriendt

Abstract:

JWST observations are providing unprecedented constraints on the history of reionization owing to the ability to detect faint galaxies at z ≫ 6. Modelling this history requires understanding both the ionizing photon production rate (ξion) and the fraction of those photons that escape into the intergalactic medium (fesc). Observational estimates of these quantities generally rely on spectroscopy for which large samples with well-defined selection functions remain limited. To overcome this challenge, we present and release a novel implicit likelihood inference pipeline, PHOTONIOn, trained on mock photometry to predict the escaped ionizing luminosity of individual galaxies (N ion) based on photometric magnitudes and redshifts. We show that PHOTONIOn is able to reliably infer N ion from photometry. This is in contrast to traditional spectral energy distribution-fitting approaches which rely on fesc prescriptions that often overpredict N ion for Lyman Continuum (LyC)-dim galaxies, even when given access to spectroscopic data. We have deployed PHOTONIOn on a sample of 4559 high-redshift galaxies from the JWST Advanced Deep Extragalactic Survey (JADES), finding gentle redshift evolutions of log10(N ion) = (0.08 ± 0.01)z + (51.60 ± 0.06) and log10(fescξion) = (0.07 ± 0.01)z + (24.12 ± 0.07). Late-time values for the ionizing photon production rate density are consistent with both theoretical models and observations. Finally, we measure the evolution of the intergalactic medium ionized fraction to find that observed populations of star-forming galaxies are capable of driving reionization in this field to completion by z ∼ 5.3 without the need for active galactic nucleus or other exotic sources, consistent with other studies of the same field. The 20 per cent of UV-brightest galaxies (MUV < −18.5) reionize roughly 35 per cent of the survey volume, demonstrating that UV faint LyC emitters are crucial for reionization.

Abstract:

<jats:p>Star formation is a key process that governs the baryon cycle within galaxies, however, the question of how it controls their growth remains elusive due to modeling uncertainties. To understand the impact of star formation models on galaxy evolution, we performed cosmological zoom-in radiation-hydrodynamic simulations of a dwarf dark matter halo, with a virial mass of <jats:italic>M</jats:italic><jats:sub>vir</jats:sub> ∼ 10<jats:sup>9</jats:sup> <jats:italic>M</jats:italic><jats:sub>⊙</jats:sub> at <jats:italic>z</jats:italic> = 6. We compared two different star formation models: a multi-freefall model combined with a local gravo-thermo-turbulent condition and a more self-consistent model based on a sink particle algorithm, where gas accretion and star formation are directly controlled by the gas kinematics. As the first study in this series, we used cosmological zoom-in simulations with different spatial resolutions and found that star formation is more bursty in the runs with the sink algorithm, generating stronger outflows than in the runs with the gravo-thermo-turbulent model. The main reason for the increased burstiness is that the gas accretion rates on the sinks are high enough to form stars on very short timescales, leading to more clustered star formation. As a result, the star-forming clumps are disrupted more quickly in the sink run due to more coherent radiation and supernova feedback. The difference in burstiness between the two star formation models becomes even more pronounced when the supernova explosion energy is artificially increased. Our results suggest that improving the modeling of star formation on small, sub-molecular cloud scales can significantly impact the global properties of simulated galaxies.</jats:p>