Clumpy disks as a testbed for feedback-regulated galaxy formation
Bibliographic record
Abstract
We study the dependence of fragmentation in massive gas-rich galaxy disks at z > 1 on stellar feedback schemes and hydrodynamical solvers, employing the GASOLINE2 SPH code and the lagrangian mesh-less code GIZMO in finite mass mode. Non-cosmological galaxy disk runs with the standard delayed-cooling blastwave feedback are compared with runs adopting a new superbubble feedback, which produces winds by modeling the detailed physics of supernova-driven bubbles and leads to efficient self-regulation of star formation. We find that, with blastwave feedback, massive star-forming clumps form in comparable number and with very similar masses in GASOLINE2 and GIZMO. Typical clump masses are in the range 107-108 M ⊙, lower than in most previous works, while giant clumps with masses above 109 M ⊙ are exceedingly rare. By contrast, superbubble feedback does not produce massive star-forming bound clumps as galaxies never undergo a phase of violent disk instability. In this scheme, only sporadic, unbound star-forming overdensities lasting a few tens of Myr can arise, triggered by non-linear perturbations from massive satellite companions. We conclude that there is severe tension between explaining massive star-forming clumps observed at z > 1 primarily as the result of disk fragmentation driven by gravitational instability and the prevailing view of feedback-regulated galaxy formation. The link between disk stability and star formation efficiency should thus be regarded as a key testing ground for galaxy formation theory.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".