Entropy-driven winds: Outflows and fountains lifted gently by buoyancy
Bibliographic record
Abstract
ABSTRACT We present a new theoretical framework for using entropy to understand how outflows driven by supernovae are launched from disc galaxies: via continuous, buoyant acceleration through the circumgalactic medium (CGM). When young star clusters detonate supernovae in the interstellar medium (ISM) of a galaxy, they generate hot, diffuse bubbles that push on the surrounding ISM and evaporate that ISM into their interiors. As these bubbles reach the scale height of the ISM, they break out of the disc, rising into the CGM. Once these bubbles break out, if they have sufficiently high entropy, they will feel an upward acceleration, owing to a local buoyant force. This upward force will accelerate these bubbles, driving them to high galactocentric radii, keeping them in the CGM for > Gyr, even if their initial velocity is much lower than the local escape velocity. We derive an equation of motion for these entropy-driven winds that connects the ISM properties, halo mass, and CGM profile of galaxies to the ultimate evolution of feedback-driven winds. We explore the parameter space of these equations, and show how this novel framework can explain both self-consistent simulations of star formation and galactic outflows as well as the new wealth of observations of CGM kinematics. We show that these entropy-driven winds can produce long wind recycling times, while still carrying a significant amount of mass. Comparisons to simulations and observations show entropy-driven winds convincingly explain the kinematics of galactic outflows.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".