Probing the dawn of galaxies: star formation and feedback in the JWST era through the GAEA model

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Abstract
The James Webb Space Telecope opened a new window for the study of the highest redshift ( z > 7) Universe. This work presents a theoretical investigation of the very high-redshift Universe using the state-of-the-art GALaxy Evolution and Assembly (GAEA) model, run on merger trees from the Planck-Millennium N -body simulation. We show that GAEA successfully reproduces a wide range of high- z observational estimates including: the galaxy stellar mass function up to z ∼ 13 and the total (galaxies and AGN) UV luminosity function (LF) up to z ∼ 10. We find that the AGN UV emission represents an important contribution at the bright end of the UVLF up to z ∼ 8, but it is negligible at higher redshift. Our model reproduces well the observed mass-metallicity relation (MZR) at z ≤ 4, while it slightly overestimates the normalization of the relation at earlier cosmic epochs. At z ≥ 11, current UVLF estimates are at least one order of magnitude larger than model predictions. We investigate the impact of different physical mechanisms, such as an enhanced star formation efficiency coupled with a reduced stellar feedback or a negligible stellar feedback at z > 10. In the framework of our model, both the galaxy stellar mass and UVLFs at z ≥ 10 can be explained by assuming feedback-free starbursts in high-density molecular clouds. However, we show that this model variant leads to a slight increase of the normalization of the z ≥ 10 MZR, strengthening the tension with available data. A model with negligible stellar feedback at z > 10 also predicts larger numbers of massive and bright galaxies aligning well with observations, but it also overestimates the metallicity of the interstellar medium. We show that these model variants can in principle be discriminated using the relation between the star formation rate and galaxy stellar mass.
Funding Information
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (PR00P2 193577)
  • Horizon 2020 (101148925)

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