Stellar feedback in galaxies and the origin of galaxy-scale winds
Bibliographic record
Abstract
Feedback from massive stars is believed to play a critical role in driving galactic super‐winds that enrich the intergalactic medium and shape the galaxy mass function, mass–metallicity relation and other global galaxy properties. In previous papers, we have introduced new numerical methods for implementing stellar feedback on sub‐giant molecular cloud (sub‐GMC) through galactic scales in numerical simulations of galaxies; the key physical processes include radiation pressure in the ultraviolet through infrared, supernovae (Type I and Type II), stellar winds (‘fast’ O star through ‘slow’ asymptotic giant branch winds), and H ii photoionization. Here, we show that these feedback mechanisms drive galactic winds with outflow rates as high as ∼10–20 times the galaxy star formation rate. The mass‐loading efficiency (wind mass‐loss rate divided by the star formation rate) scales roughly as (where Vc is the galaxy circular velocity), consistent with simple momentum‐conservation expectations. We use our suite of simulations to study the relative contribution of each feedback mechanism to the generation of galactic winds in a range of galaxy models, from Small Magellanic Cloud like dwarfs and Milky Way (MW) analogues to z∼ 2 clumpy discs. In massive, gas‐rich systems (local starbursts and high‐z galaxies), radiation pressure dominates the wind generation. By contrast, for MW‐like spirals and dwarf galaxies the gas densities are much lower and sources of shock‐heated gas such as supernovae and stellar winds dominate the production of large‐scale outflows. In all of our models, however, the winds have a complex multiphase structure that depends on the interaction between multiple feedback mechanisms operating on different spatial scales and time‐scales: any single feedback mechanism fails to reproduce the winds observed. We use our simulations to provide fitting functions to the wind mass loading and velocities as a function of galaxy properties, for use in cosmological simulations and semi‐analytic models. These differ from typically adopted formulae with an explicit dependence on the gas surface density that can be very important in both low‐density dwarf galaxies and high‐density gas‐rich galaxies.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".