Star Formation Efficiency in Nearby Galaxies Revealed with a New CO-to-H<sub>2</sub> Conversion Factor Prescription
Bibliographic record
Abstract
Abstract Determining how the galactic environment, especially the high gas densities and complex dynamics in bar-fed galaxy centers, alters the star formation efficiency (SFE) of molecular gas is critical to understanding galaxy evolution. However, these same physical or dynamical effects also alter the emissivity properties of CO, leading to variations in the CO-to-H 2 conversion factor ( α CO ) that impact the assessment of the gas column densities and thus of the SFE. To address such issues, we investigate the dependence of α CO on the local CO velocity dispersion at 150 pc scales using a new set of dust-based α CO measurements and propose a new α CO prescription that accounts for CO emissivity variations across galaxies. Based on this prescription, we estimate the SFE in a sample of 65 galaxies from the PHANGS–Atacama Large Millimeter/submillimeter Array survey. We find increasing SFE toward high-surface-density regions like galaxy centers, while using a constant or metallicity-based α CO results in a more homogeneous SFE throughout the centers and disks. Our prescription further reveals a mean molecular gas depletion time of 700 Myr in the centers of barred galaxies, which is overall three to four times shorter than in nonbarred galaxy centers or the disks. Across the galaxy disks, the depletion time is consistently around 2–3 Gyr, regardless of the choice of α CO prescription. All together, our results suggest that the high level of star formation activity in barred centers is not simply due to an increased amount of molecular gas, but also to an enhanced SFE compared to nonbarred centers or disk regions.
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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 | 0.001 | 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 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".