Frequency and nature of central molecular outflows in nearby star-forming disk galaxies
Bibliographic record
Abstract
Central molecular outflows in spiral galaxies are assumed to modulate their host galaxy’s star formation rate (SFR) by removing gas from the inner region of the galaxy. Outflows consisting of different gas phases appear to be a common feature in local galaxies, yet, little is known about the frequency of molecular outflows in main sequence galaxies in the nearby universe. We develop a rigorous set of selection criteria, which allow the reliable identification of outflows in large samples of galaxies. Our criteria make use of central spectra, position-velocity diagrams and velocity-integrated intensity maps (line-wing maps). We use this method on high-angular resolution CO (2–1) observations from the PHANGS-ALMA survey, which provides observations of the molecular gas for a homogeneous sample of 90 nearby main sequence galaxies at a resolution of ∼100 pc. We find correlations between the assigned outflow confidence and stellar mass or global SFR. We determine the frequency of central molecular outflows to be 25 ± 2% considering all outflow candidates, or 20 ± 2% for secure outflows only. Our resulting outflow candidate sample of 16−20 galaxies shows an overall enhanced fraction of active galactic nuclei (AGN) (50%) and bars (89%) compared to the full sample (galaxies with AGN: 24%, with bar: 61%). We extend the trend between mass outflow rates and SFR known for high outflow rates down to lower values (log10 Ṁout [M⊙ yr−1] < 0). Mass loading factors are of order unity, indicating that these outflows are not efficient in quenching the SFR in main sequence galaxies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".