Resolving the generation of starburst winds in Galaxy mergers
Bibliographic record
Abstract
We study galaxy superwinds driven in major mergers, using pc-scale resolution simulations with detailed models for stellar feedback that can self-consistently follow the generation of winds. The models include molecular cooling, star formation at high densities in giant molecular clouds, and gas recycling and feedback from supernovae (I and II), stellar winds and radiation pressure. We study mergers of systems from Small-Magellanic-Cloud-like dwarfs and Milky Way analogues to z ∼ 2 starburst discs. Multiphase superwinds are generated in all passages, with outflow rates up to ∼1000 M⊙ yr−1. However, the wind mass-loading efficiency (outflow rate divided by star formation rate, SFR) is similar to that in the isolated galaxy counterparts of each merger: it depends more on global galaxy properties (mass, size and escape velocity) than on the dynamical state or orbital parameters of the merger. Winds tend to be bi- or unipolar, but multiple ‘events’ build up complex morphologies with overlapping, differently oriented bubbles and shells at a range of radii. The winds have complex velocity and phase structure, with material at a range of speeds up to ∼1000 km s−1 (forming a Hubble-like flow), and a mix of molecular, ionized and hot gas that depends on galaxy properties. We examine how these different phases are connected to different feedback mechanisms. These simulations resolve a problem in some ‘subgrid’ models, where simple wind prescriptions can dramatically suppress merger-induced starbursts, often making it impossible to form Ultra Luminous Infrared Galaxies (ULIRGs). Despite large mass-loading factors (≳10–20) in the winds simulated here, the peak SFRs are comparable to those in ‘no wind’ simulations. Wind acceleration does not act equally, so cold dense gas can still lose angular momentum and form stars, while these stars blow out gas that would not have participated in the starburst in the first place. Considerable wind material is not unbound, and falls back on the disc at later times post-merger, leading to higher post-starburst SFRs in the presence of stellar feedback. We consider different simulation numerical methods and their effects on the wind phase structure; while most results are converged, we find that the existence of small clumps in the outflow at large distances from the galaxy is quite sensitive to the methodology.
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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".