Published January 20, 2025 | Version Published
Journal Article Open

The Effect of Galaxy Interactions on Starbursts in Milky Way-mass Galaxies in FIRE Simulations

  • 1. ROR icon University of Toronto
  • 2. ROR icon Canadian Institute for Theoretical Astrophysics
  • 3. Sidrat Research, 124 Merton Street, Suite 507, Toronto, ON M4S 2Z2, Canada
  • 4. Canada Research Chair in Astrophysics, Canada
  • 5. ROR icon University of California, San Diego
  • 6. ROR icon University of California, Berkeley
  • 7. ROR icon Northwestern University
  • 8. ROR icon California Institute of Technology
  • 9. ROR icon Pomona College
  • 10. ROR icon Carnegie Observatories

Abstract

Simulations and observations suggest that galaxy interactions may enhance the star formation rate (SFR) in merging galaxies. One proposed mechanism is the torque exerted on the gas and stars in the larger galaxy by the smaller galaxy. We analyze the interaction torques and star formation activity on six galaxies from the FIRE-2 simulation suite with masses comparable to the Milky Way galaxy at redshift z = 0. We trace the halos from = 3.6 to z = 0, calculating the torque exerted by the nearby galaxies on the gas in the central galaxy. We calculate the correlation between the torque and the SFR across the simulations for various mass ratios. For near-equal-stellar-mass-ratio interactions in the galaxy sample, occurring between z = 1.2−3.6, there is a positive and statistically significant correlation between the torque from nearby galaxies on the gas of the central galaxies and the SFR. For all other samples, no statistically significant correlation is found between the torque and the SFR. Our analysis shows that some, but not all, major interactions cause starbursts in the simulated Milky Way-mass galaxies, and that most starbursts are not caused by galaxy interactions. The transition from “bursty” at high redshift (z ≳ 1) to “steady” star formation state at later times is independent of the interaction history of the galaxies, and most of the interactions do not leave significant imprints on the overall trend of the star formation history of the galaxies.

Copyright and License

© 2025. 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

N.W.M. acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC; RGPIN-2023-04901). This work was performed in part at the Aspen Center for Physics, which is supported by National Science Foundation grant PHY-2210452. D.K. was supported by NSF grant AST-2108324. A.W. received support from NSF, via CAREER award AST-2045928 and grant AST-2107772, and HST grant GO-16273 from STScI. C.A.F.G. was supported by NSF through grants AST-2108230 and AST-2307327, by NASA through grant 21-ATP21-0036, and by STScI through grant JWST-AR-03252.001-A. Support for P.F.H. was provided by NSF Research Grants 1911233, 20009234, 2108318, NSF CAREER grant 1455342, NASA grants 80NSSC18K0562, HST-AR-15800. The simulations presented here used computational resources granted by the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant No. OCI-1053575, specifically allocation TG-AST120025 and resources provided by PRAC NSF.1713353 supported by the NSF; Frontera allocations AST21010 and AST20016, supported by the NSF and TACC; Blue Waters, supported by the NSF; and Pleiades, via the NASA HEC program through the NAS Division at Ames Research Center. The analysis of the FIRE simulation data was run on the CITA computing cluster “Sunnyvale.” Computations were performed on the Niagara supercomputer (M. Ponce et al. 2019) at the SciNet HPC Consortium (C. Loken et al. 2010). SciNet is funded by Innovation, Science and Economic Development Canada; the Digital Research Alliance of Canada; the Ontario Research Fund: Research Excellence; and the University of Toronto. The data used in this work were, in part, hosted on facilities supported by the Scientific Computing Core at the Flatiron Institute, a division of the Simons Foundation.

Software References

The research made use of the following software: SCIPY, 14 NUMPY 15 (S. van der Walt et al. 2011), MATPLOTLIB 16 (J. D. Hunter 2007), and YT 17 (M. J. Turk et al. 2011).

Data Availability

A public version of the GIZMO code is available at http://www.tapir.caltech.edu/~phopkins/Site/GIZMO.html. FIRE-2 simulations are publicly available (A. Wetzel et al. 2023) at http://flathub.flatironinstitute.org/fire. Additional data, including initial conditions and derived data products, are available at https://fire.northwestern.edu/data/.

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Additional details

Related works

Funding

Natural Sciences and Engineering Research Council
RGPIN-2023-04901
National Science Foundation
PHY-2210452
National Science Foundation
AST-2108324
National Science Foundation
AST-2045928
National Science Foundation
AST-2107772
Space Telescope Science Institute
GO-16273
National Science Foundation
AST-2108230
National Science Foundation
AST-2307327
National Aeronautics and Space Administration
21-ATP21-0036
Space Telescope Science Institute
JWST-AR-03252.001-A
National Science Foundation
1911233
National Science Foundation
20009234
National Science Foundation
2108318
National Science Foundation
1455342
National Aeronautics and Space Administration
80NSSC18K0562
National Aeronautics and Space Administration
HST-AR-15800
National Science Foundation
OCI-1053575

Dates

Submitted
2024-08-09
Accepted
2024-11-18
Available
2025-01-13
Published

Caltech Custom Metadata

Caltech groups
Astronomy Department, TAPIR, Walter Burke Institute for Theoretical Physics, Division of Physics, Mathematics and Astronomy (PMA)
Publication Status
Published