The Global Evolution of Giant Molecular Clouds. I. Model Formulation and Quasi‐Equilibrium Behavior
Bibliographic record
Abstract
We present semianalytic dynamical models for giant molecular clouds evolving under the influence of H II regions launched by newborn star clusters. In contrast to previous work, we neither assume that clouds are in virial or energetic equilibrium, nor do we ignore the effects of star formation feedback. The clouds, which we treat as spherical, can expand and contract homologously. Photoionization drives mass ejection; the recoil of cloud material both stirs turbulent motions and leads to an effective confining pressure. The balance between these effects and the decay of turbulent motions through isothermal shocks determines clouds' dynamical and energetic evolution. We find that for realistic values of the rates of turbulent dissipation, photoevaporation, and energy injection by H II regions, the massive clouds where most molecular gas in the Galaxy resides live for a few crossing times, in good agreement with recent observational estimates that large clouds in Local Group galaxies survive roughly 20-30 Myr. During this time clouds remain close to equilibrium, with virial parameters of 1-3 and column densities near 10 22 H atoms cm -2 , also in agreement with observed cloud properties. Over their lives they convert 5%-10% of their mass into stars, after which point most clouds are destroyed when a large H II region unbinds them. In contrast, small clouds like those found in the solar neighborhood only survive ~1 crossing time before being destroyed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".