The anatomy of a star-forming galaxy: pressure-driven regulation of star formation in simulated galaxies
Bibliographic record
Abstract
We explore the regulation of star formation in star-forming galaxies through a suite of high-resolution isolated galaxy simulations. We use the smoothed particle hydrodynamics code gasoline, including photoelectric heating and metal cooling, which produces a multi-phase interstellar medium (ISM). We show that representative star formation and feedback sub-grid models naturally lead to a weak, sub-linear dependence between the amount of star formation and changes to star formation parameters. We incorporate these sub-grid models into an equilibrium pressure-driven regulation framework. We show that the sub-linear scaling arises as a consequence of the non-linear relationship between scaleheight and the effective pressure generated by stellar feedback. Thus, simulated star formation regulation is sensitive to how well vertical structure in the ISM is resolved. Full galaxy discs experience density waves which drive locally time-dependent star formation. We develop a simple time-dependent, pressure-driven model that reproduces the response extremely well.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".