Galaxy pairs in the Sloan Digital Sky Survey – XV. Properties of ionized outflows
Bibliographic record
Abstract
ABSTRACT Powerful outflows are thought to play a critical role in galaxy evolution and black hole growth. We present the first large-scale systematic study of ionized outflows in paired galaxies and post-mergers compared to a robust control sample of isolated galaxies. We isolate the impact of the merger environment to determine if outflow properties depend on merger stage. Our sample contains ∼4000 paired galaxies and ∼250 post-mergers in the local universe (0.02 ≤ z ≤ 0.2) from the Sloan Digital Sky Survey Data Release 7 (SDSS DR 7) matched in stellar mass, redshift, local density of galaxies, and [O iii] λ5007 luminosity to a control sample of isolated galaxies. By fitting the [O iii] λ5007 line, we find ionized outflows in ∼15 per cent of our entire sample. Outflows are much rarer in star-forming galaxies compared to active galactic nuclei (AGNs), and outflow incidence and velocity increase with [O iii] λ5007 luminosity. Outflow incidence is significantly elevated in the optical + mid-infrared selected AGN compared to purely optical AGN; over 60 per cent show outflows at the highest luminosities ($L_{\mathrm{[OIII]~\lambda 5007}}\, \gtrsim$ 1042 erg s−1), suggesting mid-infrared AGN selection favours galaxies with powerful outflows, at least for higher [O iii] λ5007 luminosities. However, we find no statistically significant difference in outflow incidence, velocity, and luminosity in mergers compared to isolated galaxies, and there is no dependence on merger stage. Therefore, while interactions are predicted to drive gas inflows and subsequently trigger nuclear star formation and accretion activity, when the power source of the outflow is controlled for, the merging environment has no further impact on the large-scale ionized outflows as traced by [O iii] λ5007.
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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 | 0.001 | 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".