Galaxy pairs in the Sloan Digital Sky Survey - V. Tracing changes in star formation rate and metallicity out to separations of 80 kpc
Bibliographic record
Abstract
We present a sample of 1899 galaxies with a close companion taken from the SDSS DR7. The galaxy pairs are selected to have velocity differences < 300 km/s, projected separations (rp) < 80 kpc/h, mass ratios between 0.1 and 10, and robust measurements of star formation rates and gas-phase metallicities. We match the galaxies in total stellar mass, redshift, and local density to a set of 10 control galaxies per pair galaxy. For each pair galaxy we can therefore calculate the statistical change in star formation rate (SFR) and metallicity associated with the interaction process. Relative to the control sample, we find that galaxies in pairs show typical SFR enhancements that are, on average, 60% higher than the control sample at rp < 30 kpc/h. In addition, the pairs demonstrate more modest SFR enhancements of ~30% out to at least 80 kpc/h (the widest separations in our sample). Galaxies in both major and minor mergers show significant SFR enhancements at all rp, although the strongest starbursts (with SFR enhancements of a factor of ~10) appear to be found only in the major mergers. For the first time, we are also able to trace the metallicity changes in galaxy pairs as a function of projected separation. The metallicity is generally diluted in galaxy pairs by ~0.02 dex, with an average metallicity decrement of -0.03 dex at the smallest separations. The SFR and metallicity trends with projected separation are interpreted through a comparison with theoretical models. These simulations indicate that the peak in SFR enhancements at small separations is due to systems near the end of the merger process. The extended plateau in SFR enhancements out to at least 80 kpc/h is dominated by galaxies that have made a pericentric passage and are now experiencing triggered star formation on their trajectory towards apogalacticon, or on a subsequent close approach. (Abridged)
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".