The diversity and variability of star formation histories in models of galaxy evolution

Author:

Iyer Kartheik G12ORCID,Tacchella Sandro3ORCID,Genel Shy45,Hayward Christopher C4ORCID,Hernquist Lars3,Brooks Alyson M1,Caplar Neven6ORCID,Davé Romeel789ORCID,Diemer Benedikt310ORCID,Forbes John C4,Gawiser Eric1,Somerville Rachel S14,Starkenburg Tjitske K411

Affiliation:

1. Department of Physics and Astronomy, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854, USA

2. Dunlap Institute for Astronomy and Astrophysics, University of Toronto, 50 St George Str, Toronto, ON M5S 3H4, Canada

3. Center for Astrophysics, Harvard & Smithsonian, 60 Garden Str, Cambridge, MA 02138, USA

4. Center for Computational Astrophysics, Flatiron Institute, 162 5th Ave, New York, NY 10010, USA

5. Columbia Astrophysics Laboratory, Columbia University, 550 West 120th Str, New York, NY 10027, USA

6. Department of Astrophysical Sciences, Princeton University, 4 Ivy Ln., Princeton, NJ 08544, USA

7. South African Astronomical Observatories, Observatory, Cape Town 7925, South Africa

8. University of the Western Cape, Bellville, Cape Town 7535, South Africa

9. Institute for Astronomy, Royal Observatory, University of Edinburgh, Edinburgh EH9 3HJ, UK

10. NHFP Einstein Fellow, Department of Astronomy, University of Maryland, College Park, MD 20742, USA

11. Department of Physics & Astronomy and CIERA, Northwestern University, 2145 Sheridan Rd., Evanston, IL 60208, USA

Abstract

ABSTRACT Understanding the variability of galaxy star formation histories (SFHs) across a range of time-scales provides insight into the underlying physical processes that regulate star formation within galaxies. We compile the SFHs of galaxies at z = 0 from an extensive set of models, ranging from cosmological hydrodynamical simulations (Illustris, IllustrisTNG, Mufasa, Simba, EAGLE), zoom simulations (FIRE-2, g14, and Marvel/Justice League), semi-analytic models (Santa Cruz SAM) and empirical models (UniverseMachine), and quantify the variability of these SFHs on different time-scales using the power spectral density (PSD) formalism. We find that the PSDs are well described by broken power laws, and variability on long time-scales (≳1 Gyr) accounts for most of the power in galaxy SFHs. Most hydrodynamical models show increased variability on shorter time-scales (≲300 Myr) with decreasing stellar mass. Quenching can induce ∼0.4−1 dex of additional power on time-scales >1 Gyr. The dark matter accretion histories of galaxies have remarkably self-similar PSDs and are coherent with the in situ star formation on time-scales >3 Gyr. There is considerable diversity among the different models in their (i) power due to star formation rate variability at a given time-scale, (ii) amount of correlation with adjacent time-scales (PSD slope), (iii) evolution of median PSDs with stellar mass, and (iv) presence and locations of breaks in the PSDs. The PSD framework is a useful space to study the SFHs of galaxies since model predictions vary widely. Observational constraints in this space will help constrain the relative strengths of the physical processes responsible for this variability.

Funder

National Aeronautics and Space Administration

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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