SDSS-IV MaNGA: The Radial Profile of Enhanced Star Formation in Close Galaxy Pairs
Bibliographic record
Abstract
Abstract We compare the radial profiles of the specific star formation rate (sSFR) in a sample of 169 star-forming galaxies in close pairs with those of mass-matched control galaxies in the SDSS-IV MaNGA survey. We find that the sSFR is centrally enhanced (within one effective radius) in interacting galaxies by ∼0.3 dex and that there is a weak sSFR suppression in the outskirts of the galaxies of ∼0.1 dex. We stack the difference profiles for galaxies in five stellar-mass bins in the range log( M / M ⊙ ) = 9.0–11.5 and find that the sSFR enhancement has no dependence on the stellar mass. The same result is obtained when comparison galaxies are matched to each paired galaxy in both stellar mass and redshift. In addition, we find that the sSFR enhancement is elevated in pairs with nearly equal masses and closer projected separations, in agreement with previous work based on single-fiber spectroscopy. We also find that the sSFR offsets in the outskirts of the paired galaxies are dependent on whether the galaxy is the more-massive or less-massive companion in the pair. The more-massive companion experiences zero to a positive sSFR enhancement, while the less-massive companion experiences sSFR suppression in their outskirts. Our results illustrate the complex tidal effects on star formation in closely paired galaxies.
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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 | 0.001 |
| 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".