Molecular Gas and Star Formation in Nearby Galaxy Centers
Bibliographic record
Abstract
Star formation in galaxies is governed by the amount of molecular gas and the efficiency that gas is converted into stars. However, assessing the amount of molecular gas relies on the CO-to-H2 conversion factor (alpha_CO), which is known to vary with molecular gas conditions like density, temperature, and dynamical state -- the same conditions that also alter star formation efficiency. The variation of alpha_CO, particularly in galaxy centers where alpha_CO can drop by nearly an order of magnitude, thus causes major uncertainties in current molecular gas and star formation efficiency measurements. Using ALMA observations of multiple low-J 12CO, 13CO, and C18O lines in several barred galaxy centers, we found that alpha_CO is primarily driven by CO opacity changes and therefore shows strong correlations with observables like velocity dispersion and 12CO/13CO line ratio. Motivated by these results, we have constructed a new alpha_CO prescription which accounts for emissivity effects in galaxy centers and verified it on a set of barred and non-barred galaxies with measured alpha_CO values from dust. Applying our new prescription to 65 galaxies from the PHANGS-ALMA survey, we found an overall three times higher star formation efficiency in barred galaxy centers than in non-barred galaxy centers, and such a trend is obscured when using a constant alpha_CO or other existing prescriptions. Our results suggest that the high star formation rate observed in barred galaxy centers is due to an enhanced star formation efficiency compared to non-barred galaxy centers or the disk regions, rather than a substantially increased amount of molecular gas in barred galaxy centers.
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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) | 0.001 | 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".