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Published March 2022 | Submitted + Published
Journal Article Open

High-redshift predictions from IllustrisTNG – III. Infrared luminosity functions, obscured star formation, and dust temperature of high-redshift galaxies

Abstract

We post-process galaxies in the IllustrisTNG simulations with SKIRT radiative transfer calculations to make predictions for the rest-frame near-infrared (NIR) and far-infrared (FIR) properties of galaxies at z ≥ 4. The rest-frame K- and z-band galaxy luminosity functions from TNG are overall consistent with observations, despite ∼0.5dex underprediction at z = 4 for M_K ≲ −25 and M_z ≲ −24. Predictions for the JWST MIRI observed galaxy luminosity functions and number counts are given. Based on theoretical estimations, we show that the next-generation survey conducted by JWST can detect 500 (30) galaxies in F1000W in a survey area of 500arcmin² at z = 6 (z = 8). As opposed to the consistency in the UV, optical, and NIR, we find that TNG, combined with our dust modelling choices, significantly underpredicts the abundance of most dust-obscured and thus most luminous FIR galaxies. As a result, the obscured cosmic star formation rate density (SFRD) and the SFRD contributed by optical/NIR dark objects are underpredicted. The discrepancies discovered here could provide new constraints on the sub-grid feedback models, or the dust contents, of simulations. Meanwhile, although the TNG predicted dust temperature and its relations with IR luminosity and redshift are qualitatively consistent with observations, the peak dust temperature of z ≥ 6 galaxies are overestimated by about 20K⁠. This could be related to the limited mass resolution of our simulations to fully resolve the porosity of the interstellar medium (or specifically its dust content) at these redshifts.

Additional Information

© 2022 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model). Accepted 2021 December 22. Received 2021 November 24; in original form 2021 April 26. Published: 04 January 2022. MV acknowledges support through the National Aeronautics and Space Administration (NASA) Astrophysics Theory Program (ATP) grants 16-ATP16-0167, 19-ATP19-0019, 19-ATP19-0020, 19-ATP19-0167, and the National Science Foundation (NSF) grants AST-1814053, AST-1814259, AST-1909831, and AST-2007355. ST is supported by the Smithsonian Astrophysical Observatory through the Center for Astrophysics (CfA) Fellowship. PT acknowledges support from NSF grant AST-2008490. FM acknowledges support through the Program 'Rita Levi Montalcini' of the Italian MUR. The primary TNG simulations were realized with compute time granted by the Gauss Centre for Super-computing (GCS): TNG50 under GCS Large-Scale Project GCS-DWAR (2016; PIs Nelson/Pillepich), and TNG100 and TNG300 under GCS-ILLU (2014; PI Springel) on the GCS share of the supercomputer Hazel Hen at the High Performance Computing Center Stuttgart (HLRS). Data Availability: The simulation data of the IllustrisTNG project is publicly available at https://www.tng-project.org/data/. The analysis data of this work was generated and stored on the super-computing system Cannon at Harvard University. The data underlying this article can be shared on a reasonable request to the corresponding author.

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Additional details

Created:
August 20, 2023
Modified:
October 23, 2023