Galaxy pairs in the Sloan Digital Sky Survey – VI. The orbital extent of enhanced star formation in interacting galaxies
Bibliographic record
Abstract
Abstract We use pair and environmental classifications of ∼211 000 star-forming galaxies from the Sloan Digital Sky Survey, along with a suite of merger simulations, to investigate the enhancement of star formation as a function of separation in galaxy pairs. Using a new technique for distinguishing between the influence of nearby neighbours and larger scale environment, we find a clear enhancement in star formation out to projected separations of ∼150 kpc, beyond which there is no net enhancement. We find the strongest enhancements at the smallest separations (especially <20 kpc), consistent with earlier work. Similar trends are seen in the simulations, which indicate that the strongest enhancements are produced in highly disturbed systems approaching final coalescence, whereas the more modest enhancements seen at wider separations are the result of starburst activity triggered at first pericentre passage, which persists as the galaxies move to larger separations. The absence of any net enhancement beyond 150 kpc provides reassurance that the detected enhancements are due to galaxy–galaxy interactions, rather than larger scale environmental effects or potential pair selection biases. A rough census indicates that 66 per cent of the enhanced star formation in our pair sample occurs at separations >30 kpc. We conclude that significant interaction-induced star formation is not restricted to merger remnants or galaxies with close companions; instead, a larger population of wider separation pairs exhibit enhanced star formation due to recent close encounters.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".