Dynamical Equilibrium in the Molecular ISM in 28 Nearby Star-forming Galaxies
Bibliographic record
Abstract
Abstract We compare the observed turbulent pressure in molecular gas, P turb , to the required pressure for the interstellar gas to stay in equilibrium in the gravitational potential of a galaxy, P DE . To do this, we combine arcsecond resolution CO data from PHANGS-ALMA with multiwavelength data that trace the atomic gas, stellar structure, and star formation rate (SFR) for 28 nearby star-forming galaxies. We find that P turb correlates with—but almost always exceeds—the estimated P DE on kiloparsec scales. This indicates that the molecular gas is overpressurized relative to the large-scale environment. We show that this overpressurization can be explained by the clumpy nature of molecular gas; a revised estimate of P DE on cloud scales, which accounts for molecular gas self-gravity, external gravity, and ambient pressure, agrees well with the observed P turb in galaxy disks. We also find that molecular gas with cloud-scale in our sample is more likely to be self-gravitating, whereas gas at lower pressure it appears more influenced by ambient pressure and/or external gravity. Furthermore, we show that the ratio between P turb and the observed SFR surface density, , is compatible with stellar feedback-driven momentum injection in most cases, while a subset of the regions may show evidence of turbulence driven by additional sources. The correlation between and kpc-scale P DE in galaxy disks is consistent with the expectation from self-regulated star formation models. Finally, we confirm the empirical correlation between molecular-to-atomic gas ratio and kpc-scale P DE reported in previous works.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".