Cosmological galaxy evolution with superbubble feedback – II. The limits of supernovae
Bibliographic record
Abstract
We explore when supernovae can (and cannot) regulate the star formation and bulge growth in galaxies based on a sample of 18 simulated galaxies. The simulations are the first to model feedback superbubbles including evaporation and conduction. These processes determine the mass loadings and wind speeds of galactic outflows. We show that for galaxies with virial masses >1012 M⊙, supernovae alone cannot prevent excessive star formation. This occurs due to a shutdown of galactic winds, with wind mass loadings falling from η ∼ 10 to η < 1. In more massive systems, the ejection of baryons to the circumgalactic medium falters earlier on and the galaxies diverge significantly from observed galaxy scaling relations and morphologies. The decreasing efficiency is due to a deepening potential well preventing gas escape, and is unavoidable if mass-loaded outflows regulate star formation on galactic scales. This implies that non-supernova feedback mechanisms must become dominant for galaxies with stellar masses greater than ∼4 × 1010 M⊙. The runaway growth of the central stellar bulge, strongly linked to black hole growth, suggests that feedback from active galactic nuclei is the likely mechanism. Below this mass, supernovae alone are able to produce a realistic stellar mass fraction, star formation history and disc morphology.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".