Galaxy Mergers up to Z < 2.5. I. The Star Formation Properties of Merging Galaxies at Separations of 3–15 kpc
Bibliographic record
Abstract
Abstract We present a study of the influence of galaxy mergers on star formation at 0.3 < z < 2.5. Major mergers are selected from the CANDELS/3D-HST catalog using a peak-finding algorithm. Mergers have projected galaxy nucleus separation of their members between 3 and 15 kpc. We compare the star formation activity in merging and nonmerging galaxies and find no significant differences. We find that only 12% of the galaxies in major mergers (in which both galaxies have ) are starbursting (i.e., with star formation rate (SFR) above the main sequence of star-forming galaxies by >0.5 dex). Merging galaxies, which include galaxies with lower masses, show a higher fraction of starbursting galaxies (20%). The low fraction of starbursting merging galaxies in this sample suggests that at galaxy nucleus separations of 3–15 kpc merging galaxies are still in an early stage and are yet to reach the maximum level of star formation activity. Furthermore, the level of star formation enhancement and its duration could be arguably reduced compared to local mergers, as shown by simulations of high-z mergers, and might also depend on the physical properties (such as stellar mass and gas fraction) of the merging galaxies. Finally, we compare the specific SFR between merging galaxies. Our results suggest that, as the mass of the merging galaxies increases, the star formation activity in the less massive member in the merger suffers a more dramatic impact than its companion galaxy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".