THE DISRUPTION OF GIANT MOLECULAR CLOUDS BY RADIATION PRESSURE & THE EFFICIENCY OF STAR FORMATION IN GALAXIES
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Bibliographic record
Abstract
Star formation is slow, in the sense that the gas consumption time is much longer than the dynamical time. It is also inefficient; essentially all star formation in local galaxies takes place in giant molecular clouds (GMCs), but the fraction of a GMC converted to stars is very small, ~5%. In the most luminous starbursts, the GMC lifetime is shorter than the main sequence lifetime of even the most massive stars, so that supernovae can play no role in GMC disruption. We investigate the disruption of GMCs across a wide range of galaxies, from normal spirals to the densest starbursts; we take into account the effects of HII gas pressure, shocked stellar winds, protostellar jets, and radiation pressure produced by the absorption and scattering of starlight on dust grains. In the Milky Way, we find that a combination of three mechanisms, jets, HII gas pressure, and radiation pressure, disrupts the clouds. In more rapidly star forming galaxies such as ``clump'' galaxies at high-redshift, ultra-luminous infrared galaxies (ULIRGs) and submillimeter galaxies, radiation pressure dominates natal cloud distribution. We predict the presence of 10-20 clusters with masses ~10^7 Msun in local ULIRGs such as Arp 220 and a similar number of clusters with M_* ~ 10^8 Msun in high redshift clump galaxies; submillimeter galaxies will have even more massive clusters. We find that the mass fraction of a GMC that ends up in stars is an increasing function of the gas surface density of a galaxy, reaching ~35% in the most luminous starbursts. Furthermore, the disruption of bubbles by radiation pressure stirs the interstellar medium to velocities of ~10 km/s in normal galaxies and to ~100 km/s in ULIRGs like Arp 220, consistent with observations. Thus, radiation pressure may play a dominant role in the ISM of star-forming galaxies.
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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 | 0.000 |
| 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 it