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Title: The thesan project: Lyman-α emitter luminosity function calibration

The observability of Lyα emitting galaxies (LAEs) during the Epoch of Reionization can provide a sensitive probe of the evolving neutral hydrogen gas distribution, thus setting valuable constraints to distinguish different reionization models. In this study, we utilize the new thesan suite of large-volume ($L_\text{box} = 95.5\, \text{cMpc}$) cosmological radiation-hydrodynamic simulations to directly model the Lyα emission from individual galaxies and the subsequent transmission through the intergalactic medium. thesan combines the arepo-rt radiation-hydrodynamic solver with the IllustrisTNG galaxy formation model and includes high- and medium-resolution simulations designed to investigate the impacts of halo-mass-dependent escape fractions, alternative dark matter models, and numerical convergence. We find important differences in the Lyα transmission based on reionization history, bubble morphology, frequency offset from line centre, and galaxy brightness. For a given global neutral fraction, Lyα transmission reduces when low-mass haloes dominate reionization over high-mass haloes. Furthermore, the variation across sightlines for a single galaxy is greater than the variation across all galaxies. This collectively affects the visibility of LAEs, directly impacting observed Lyα luminosity functions (LFs). We employ Gaussian Process Regression using SWIFTEmulator to rapidly constrain an empirical model for dust escape fractions and emergent spectral-line profiles to match observed LFs. We find that dust strongly impacts the Lyα transmission and covering fractions of MUV ≲ −19 galaxies in $M_\text{vir} \gtrsim 10^{11}\, \text{M}_{\bigodot }$ haloes, such that the dominant mode of removing Lyα photons in non-LAEs changes from low-IGM transmission to high dust absorption around z ∼ 7.

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Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Monthly Notices of the Royal Astronomical Society
Page Range / eLocation ID:
p. 4356-4374
Medium: X
Sponsoring Org:
National Science Foundation
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