Bursty Star Formation Naturally Explains the Abundance of Bright Galaxies at Cosmic Dawn
Abstract
Recent discoveries of a significant population of bright galaxies at cosmic dawn (z ≳ 10) have enabled critical tests of cosmological galaxy formation models. In particular, the bright end of the galaxys' UV luminosity functions (UVLFs) appear higher than predicted by many models. Using approximately 25,000 galaxy snapshots at 8 ≤ z ≤ 12 in a suite of FIRE-2 cosmological "zoom-in" simulations from the Feedback in Realistic Environments (FIRE) project, we show that the observed abundance of UV-bright galaxies at cosmic dawn is reproduced in these simulations with a multichannel implementation of standard stellar feedback processes, without any fine-tuning. Notably, we find no need to invoke previously suggested modifications, such as a nonstandard cosmology, a top-heavy stellar initial mass function, or a strongly enhanced star formation efficiency. We contrast the UVLFs predicted by bursty star formation in these original simulations to those derived from star formation histories (SFHs) smoothed over prescribed timescales (e.g., 100 Myr). The comparison demonstrates that the strongly time-variable SFHs predicted by the FIRE simulations play a key role in correctly reproducing the observed, bright-end UVLFs at cosmic dawn: the bursty SFHs induce order-or-magnitude changes in the abundance of UV-bright (MUV ≲ −20) galaxies at z ≳ 10. The predicted bright-end UVLFs are consistent with both the spectroscopically confirmed population and the photometrically selected candidates. We also find good agreement between the predicted and observationally inferred integrated UV luminosity densities, which evolve more weakly with redshift in FIRE than suggested by some other models.
Copyright and License
© 2023. The Author(s). Published by the American Astronomical Society.
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Acknowledgement
The authors thank the anonymous reviewer for comments that helped improve this Letter, as well as Pratik Gandhi, Yuichi Harikane, and Julian Muñoz for helpful discussion. G.S. was supported by a CIERA Postdoctoral Fellowship. C.A.F.G. was supported by NSF through grants AST-2108230 and CAREER award AST-1652522; by NASA through grants 17-ATP17-0067 and 21-ATP21-0036; by STScI through grant HST-GO-16730.016-A; and by CXO through grant TM2-23005X. The Flatiron Institute is supported by the Simons Foundation. A.W. received support from NSF via CAREER award AST-2045928 and grant AST-2107772; NASA ATP grant 80NSSC20K0513; and HST grants AR-15809, GO-15902, GO-16273 from STScI. The simulations used in this Letter were run on XSEDE computational resources (allocations TG-AST120025, TG-AST130039, TG-AST140023, and TG-AST140064). Additional analysis was done using the Quest computing cluster at Northwestern University.
Software References
BPASS (Eldridge et al. 2017), GizmoAnalysis (Wetzel et al. 2016; Wetzel & Garrison-Kimmel 2020), hmf (Murray et al. 2013).
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Additional details
- Northwestern University
- CIERA Postdoctoral Fellowship
- National Science Foundation
- AST-2108230
- National Science Foundation
- AST-165252
- National Aeronautics and Space Administration
- 17-ATP17-0067
- National Aeronautics and Space Administration
- 21-ATP21-0036
- Space Telescope Science Institute
- HST-GO-16730.016-A
- National Aeronautics and Space Administration
- TM2-23005X
- Simons Foundation
- National Science Foundation
- AST-2045928
- National Science Foundation
- AST-2107772
- National Aeronautics and Space Administration
- 80NSSC20K0513
- Space Telescope Science Institute
- AR-15809
- Space Telescope Science Institute
- GO-15902
- Space Telescope Science Institute
- GO-16273
- Accepted
-
2023-09-09Accepted
- Available
-
2023-10-03Published
- Caltech groups
- TAPIR
- Publication Status
- Published