ULTRAVIOLET ESCAPE FRACTIONS FROM GIANT MOLECULAR CLOUDS DURING EARLY CLUSTER FORMATION
Bibliographic record
Abstract
ABSTRACT The UV photon escape fraction from molecular clouds is a key parameter for understanding the ionization of the interstellar medium and extragalactic processes such as cosmic reionization. We present the ionizing photon flux and the corresponding photon escape fraction (f esc) arising as a consequence of star cluster formation in a turbulent, 106 M ⊙ giant molecular cloud, simulated using the code FLASH. We make use of sink particles to represent young, star-forming clusters coupled with a radiative transfer scheme to calculate the emergent UV flux. We find that the ionizing photon flux across the cloud boundary is highly variable in time and space due to the turbulent nature of the intervening gas. The escaping photon fraction remains at ∼5% for the first 2.5 Myr, followed by two pronounced peaks at 3.25 and 3.8 Myr with a maximum f esc of 30% and 37%, respectively. These peaks are due to the formation of large H ii regions that expand into regions of lower density, some of which reaching the cloud surface. However, these phases are short-lived, and f esc drops sharply as the H ii regions are quenched by the central cluster passing through high-density material due to the turbulent nature of the cloud. We find an average f esc of 15% with factor of two variations over 1 Myr timescales. Our results suggest that assuming a single value for f esc from a molecular cloud is in general a poor approximation, and that the dynamical evolution of the system leads to large temporal variation.
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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 | 0.000 | 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 | 0.000 |
| 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".