RADIATION PRESSURE FROM MASSIVE STAR CLUSTERS AS A LAUNCHING MECHANISM FOR SUPER-GALACTIC WINDS
Bibliographic record
Abstract
Galactic outflows of cool (∼10 4 K) gas are ubiquitous in local starburst galaxies and in most high-redshift galaxies. Hot gas from supernovae has long been suspected as the primary driver, but this mechanism suffers from its tendency to destroy the cool gas. We propose a modification of the supernova scenario that overcomes this difficulty. Star formation is observed to take place in clusters. We show that, for L ⋆ galaxies, the radiation pressure from clusters with M cl ≳ 10 6 M ☉ is able to expel the surrounding gas at velocities in excess of the circular velocity v c of the disk galaxy. This cool gas travels above the galactic disk before supernovae erupt in the driving cluster. Once above the disk, the cool outflowing gas is exposed to radiation and hot gas outflows from the galactic disk, which in combination drive it to distances of ∼50 kpc. Because the radiatively driven clouds grow in size as they travel, and because the hot gas is more dilute at large distance, the clouds are less subject to destruction. Therefore, unlike wind-driven clouds, radiatively driven clouds can give rise to the metal absorbers seen in quasar spectra. We identify these cluster-driven winds with large-scale galactic outflows. The maximum cluster mass in a galaxy is an increasing function of the galaxy's gas surface density, so only starburst galaxies are able to drive cold outflows. We find the critical star formation rate for launching large-scale cool outflows to be , in good agreement with observations.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".