RADIATION PRESSURE FROM MASSIVE STAR CLUSTERS AS A LAUNCHING MECHANISM FOR SUPER-GALACTIC WINDS
Bibliographic record
Abstract
Galactic outflows of low ionization, cool gas are ubiquitous in local starburst galaxies, and in the majority of galaxies at high redshift. How these cool outflows arise is still in question. Hot gas from supernovae has long been suspected as the primary driver, but this mechanism suffers from its tendency to destroy the cool gas as the latter is accelerated. We propose a modification of the supernova scenario that overcomes this difficulty. Star formation is observed to take place in clusters; in a given galaxy, the bulk of the star formation is found in the ~20 most massive clusters. We show that, for L* galaxies, the radiation pressure from clusters with M>10^6 M_sun is able to expel the surrounding gas at velocities in excess of the circular velocity of the disk galaxy. This cool gas can travel above the galactic disk in less than 2 Myr, well before any supernovae erupt in the driving cluster. Once above the disk, the cool outflowing gas is exposed to radiation, and supernovae induced hot gas outflows, from other clusters in the disk, which drive it to distances of several tens to hundreds of 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 if they do eventually encounter hot gas. Therefore, unlike wind driven clouds, radiatively driven clouds can survive to distances ~50 kpc. We identify these cluster-driven winds with large-scale galactic outflows. Another implication of our model is that only starburst galaxies, where massive clusters reside, are able to drive winds cold outflows on galactic scales via this mechanism. We find that the critical star formation rates above which large scale cool outflows will be launched to be ~0.1 M_sun/yr/kpc^2, which is in good agreement with observations.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".