History of Galaxy Interactions and their Impact on Star Formation over the Last 7 Gyr from GEMS
Shardha Jogee, Sarah H. Miller, Kyle Penner, Rosalind E. Skelton,, Christopher J. Conselice, Rachel S. Somerville, Eric F.Bell, Xian Zhong, Zheng, Hans-Walter Rix, Aday R. Robaina, Fabio D. Barazza, Marco Barden,, Andrea Borch, Steven V.W. Beckwith, John A. R. Caldwell

TL;DR
This study estimates galaxy merger frequencies and their effects on star formation over the last 7 billion years, finding mergers are common but only modestly influence star formation rates, with most driven by non-interacting galaxies.
Contribution
It provides the first empirical estimates of minor merger frequencies at z<1 and compares observed merger rates with various theoretical models.
Findings
Approximately 68% of high mass galaxies experienced mergers of mass ratio >1/10.
Merger rates from models bracket observed data, showing a fivefold dispersion.
Visibly merging systems contribute less than 30% to the cosmic star formation rate density.
Abstract
We perform a comprehensive estimate of the frequency of galaxy mergers and their impact on star formation over z~0.24--0.80 (lookback time T_b~3--7 Gyr) using 3698 (M*>=1e9 Msun) galaxies with GEMS HST, COMBO-17, and Spitzer data. Our results are: (1) Among 790 high mass (M*>=2.5e10 Msun) galaxies, the visually-based merger fraction over z~0.24--0.80, ranges from 9%+-5% to 8%+-2%. Lower limits on the major and minor merger fractions over this interval range from 1.1% to 3.5%, and 3.6% to 7.5%, respectively. This is the first approximate empirical estimate of the frequency of minor mergers at z<1. For a visibility timescale of ~0.5 Gyr, it follows that over T_b~3--7 Gyr, ~68% of high mass systems have undergone a merger of mass ratio >1/10, with ~16%, 45%, and 7% of these corresponding respectively to major, minor, and ambiguous `major or minor' mergers. The mean merger rate is a few x…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
