Masses, Star-Formation Efficiencies, and Dynamical Evolution of 18,000 HII Regions
Bibliographic record
Abstract
We present measurements of the masses associated with $\sim18,000$ HII regions across 19 nearby star-forming galaxies by combining data from JWST, HST, MUSE, ALMA, VLA, and MeerKAT from the multi-wavelength PHANGS survey. We report 10 pc-scale measurements of the mass of young stars, ionized gas, and older disk stars coincident with each HII region, as well as the initial and current mass of molecular gas, atomic gas, and swept-up shell material, estimated from lower resolution data. We find that the mass of older stars dominates over young stars at $\gtrsim10\rm\,pc$ scales, and ionized gas exceeds the stellar mass in most optically bright HII regions. Combining our mass measurements for a statistically large sample of HII regions, we derive 10 pc scale star-formation efficiencies $\approx6{-}17\%$ for individual HII regions. Comparing each region's self-gravity with the ambient ISM pressure and total pressure from pre-supernova stellar feedback, we show that most optically bright HII regions are over-pressured relative to their own self-gravity and the ambient ISM pressure, and that they are hence likely expanding into their surroundings. Larger HII regions in galaxy centers approach dynamical equilibrium. The self-gravity of regions is expected to dominate over pre-supernova stellar feedback pressure at $\gtrsim130\rm\,pc$ and $60\rm\,pc$ scales in galaxy disks and centers, respectively, but is always sub-dominant to the ambient ISM pressure on HII region scales. Our measurements have direct implications for the dynamical evolution of star-forming regions and the efficiency of stellar feedback in ionizing and clearing cold gas.
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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 | 0.000 | 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".