Stellar feedback and bulge formation in clumpy discs
Bibliographic record
Abstract
We use numerical simulations of isolated galaxies to study the effects of stellar feedback on the formation and evolution of giant star-forming gas ‘clumps’ in high-redshift, gas-rich galaxies. Such galactic discs are unstable to the formation of bound gas-rich clumps whose properties initially depend only on global disc properties, not the microphysics of feedback. In simulations without stellar feedback, clumps turn an order-unity fraction of their mass into stars and sink to the centre, forming a large bulge and kicking most of the stars out into a much more extended stellar envelope. By contrast, strong radiative stellar feedback disrupts even the most massive clumps after they turn ∼10–20 per cent of their mass into stars, in a time-scale of ∼10–100 Myr, ejecting some material into a superwind and recycling the rest of the gas into the diffuse interstellar medium (ISM). This suppresses the bulge formation rate by direct ‘clump coalescence’ by a factor of several. However, the galactic discs do undergo significant internal evolution in the absence of mergers: clumps form and disrupt continuously and torque gas to the galactic centre. The resulting evolution is qualitatively similar to bar/spiral evolution in simulations with a more homogeneous ISM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".