Abstract
Observations and simulations of interacting galaxies and mergers in the local universe have shown that interactions can significantly enhance the star formation rates (SFRs) and fueling of active galactic nuclei (AGN). However, at higher redshift, some simulations suggest that the level of star formation enhancement induced by interactions is lower due to the higher gas fractions and already increased SFRs in these galaxies. To test this, we measure the SFR enhancement in a total of 2351 (1327) massive (M * > 1010 M ⊙) major (1 < M 1/M 2 < 4) spectroscopic galaxy pairs at 0.5 < z < 3.0 with ΔV < 5000 km s−1 (1000 km s−1) and projected separation <150 kpc selected from the extensive spectroscopic coverage in the COSMOS and CANDELS fields. We find that the highest level of SFR enhancement is a factor of 1.23 − 0.09 + 0.08 in the closest projected separation bin (<25 kpc) relative to a stellar mass-, redshift-, and environment-matched control sample of isolated galaxies. We find that the level of SFR enhancement is a factor of ∼1.5 higher at 0.5 < z < 1 than at 1 < z < 3 in the closest projected separation bin. Among a sample of visually identified mergers, we find an enhancement of a factor of 1.86 − 0.18 + 0.29 (∼3σ) for coalesced systems. For this visually identified sample, we see a clear trend of increased SFR enhancement with decreasing projected separation (2.40 − 0.37 + 0.62 versus 1.58 − 0.20 + 0.29 for 0.5 < z < 1.6 and 1.6 < z < 3.0, respectively). The SFR enhancements seen in our interactions and mergers are all lower than the level seen in local samples at the same separation, suggesting that the level of interaction-induced star formation evolves significantly over this time period.
| Original language | English (US) |
|---|---|
| Article number | 4 |
| Journal | Astrophysical Journal |
| Volume | 940 |
| Issue number | 1 |
| DOIs | |
| State | Published - Nov 1 2022 |
Bibliographical note
Funding Information:Based in part on observations obtained at the international Gemini Observatory and processed using the Gemini IRAF package, a program of NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation on behalf of the Gemini Observatory partnership: the National Science Foundation (United States), National Research Council (Canada), Agencia Nacional de Investigación y Desarrollo (Chile), Ministerio de Ciencia, Tecnología e Innovación (Argentina), Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain.
Funding Information:
This work was supported by a NASA Keck PI Data Award, administered by the NASA Exoplanet Science Institute. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.
Funding Information:
Support for this work was provided by NASA through grants HST-GO-13657.010-A and HST-AR-14298.004-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. Support was also provided by NASA through grant NNX16AB36G as part of the Astrophysics Data Analysis Program. This work was also supported by start-up funds and the Dean’s Research Initiation Grant fund from the Rochester Institute of Technology’s College of Science. Spectral energy distribution fitting was performed using the computational resources and support from Research Computing Services at the Rochester Institute of Technology (Rochester Institute of Technology 2019). E.S. thanks the LSSTC Data Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining grant No. 1829740, the Brinson Foundation, and the Moore Foundation. The participation of E.S. in the program has benefited this work. D.R.P. acknowledges financial support from NSERC of Canada. E.T. acknowledges support from CATA-Basal AFB170002 and FB210003, FONDECYT regular grant 1190818, and Millennium Nucleus NCN19_058 (TITANs). B.L. acknowledges support from the National Aeronautics and Space Administration under NASA grant No. 80NSSC21K0986. This paper does not reflect the views or opinions of the National Science Foundation or the American Association for the Advancement of Science (AAAS).
Funding Information:
Based in part on observations made with the NASA/ESA Hubble Space Telescope, obtained from the Data Archive at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. This work is based in part on observations made with the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA.
Funding Information:
Support for this work was provided by NASA through grants HST-GO-13657.010-A and HST-AR-14298.004-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. Support was also provided by NASA through grant NNX16AB36G as part of the Astrophysics Data Analysis Program. This work was also supported by start-up funds and the Dean’s Research Initiation Grant fund from the Rochester Institute of Technology’s College of Science. Spectral energy distribution fitting was performed using the computational resources and support from Research Computing Services at the Rochester Institute of Technology (Rochester Institute of Technology ). E.S. thanks the LSSTC Data Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining grant No. 1829740, the Brinson Foundation, and the Moore Foundation. The participation of E.S. in the program has benefited this work. D.R.P. acknowledges financial support from NSERC of Canada. E.T. acknowledges support from CATA-Basal AFB170002 and FB210003, FONDECYT regular grant 1190818, and Millennium Nucleus NCN19_058 (TITANs). B.L. acknowledges support from the National Aeronautics and Space Administration under NASA grant No. 80NSSC21K0986. This paper does not reflect the views or opinions of the National Science Foundation or the American Association for the Advancement of Science (AAAS).
Publisher Copyright:
© 2022. The Author(s). Published by the American Astronomical Society.
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