A superbubble feedback model for galaxy simulations
Bibliographic record
Abstract
We present a new stellar feedback model that reproduces superbubbles. Superbubbles from clustered young stars evolve quite differently to individual supernovae and are substantially more efficient at generating gas motions. The essential new components of the model are thermal conduction, subgrid evaporation and a subgrid multiphase treatment for cases where the simulation mass resolution is insufficient to model the early stages of the superbubble. The multiphase stage is short compared to superbubble lifetimes. Thermal conduction physically regulates the hot gas mass without requiring a free parameter. Accurately following the hot component naturally avoids overcooling. Prior approaches tend to heat too much mass, leaving the hot interstellar medium (ISM) below 106 K and susceptible to rapid cooling unless ad hoc fixes were used. The hot phase also allows feedback energy to correctly accumulate from multiple, clustered sources, including stellar winds and supernovae. We employ high-resolution simulations of a single star cluster to show the model is insensitive to numerical resolution, unresolved ISM structure and suppression of conduction by magnetic fields. We also simulate a Milky Way analogue and a dwarf galaxy. Both galaxies show regulated star formation and produce strong outflows.
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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 | 0.000 | 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 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".