In-n-out: The Gas Cycle From Dwarfs To Spiral Galaxies
Bibliographic record
Abstract
We examine the scalings of galactic outflows with halo mass across a suite of 20 high-resolution cosmological zoom galaxy simulations covering halo masses in the range 10^9.5-10^12\\M. These simulations self-consistently generate outflows from the available supernova energy in a manner that successfully reproduces key galaxy observables, including the stellar mass–halo mass, Tully–Fisher, and mass–metallicity relations. We quantify the importance of ejective feedback to setting the stellar mass relative to the efficiency of gas accretion and star formation. Ejective feedback is increasingly important as galaxy mass decreases; we find an effective mass loading factor that scales as v-circ-2.2, with an amplitude and shape that are invariant with redshift. These scalings are consistent with analytic models for energy-driven wind, based solely on the halo potential. Recycling is common: about half of the outflow mass across all galaxy masses is later reaccreted. The recycling timescale is typically ~1 Gyr, virtually independent of halo mass. Recycled material is reaccreted farther out in the disk and with typically ~2–3 times more angular momentum. These results elucidate and quantify how the baryon cycle plausibly regulates star formation and alters the angular momentum distribution of disk material across the halo mass range where most cosmic star formation occurs.
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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 | 0.000 | 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".