DAMPED LYα ABSORBER KINEMATICS AND OUTFLOWS FROM STARBURST GALAXIES
Bibliographic record
Abstract
We present results from a numerical study of the multiphase interstellar medium in sub-Lyman-break galaxy protogalactic clumps. Such clumps are abundant at z = 3 and are thought to be a major contributor to damped Lyα absorption. We model the formation of winds from these clumps and show that during star formation (SF) episodes they feature outflows with neutral gas velocity widths up to several hundred km s -1 . Such outflows might, in principle, produce the high velocity dispersion observed in damped Lyα absorbers (DLAs). Since the majority of DLAs have low SF rates, and only a small fraction of them might host a starburst at any given time, our median velocity width v 90 still falls short of the observed value. This discrepancy with observations could indicate that at l = 12 pc grid resolution the efficiency of conversion of feedback energy into hydrodynamical flows is less than optimal, even though these models show a remarkable improvement compared to the lower resolution runs. At l = 24 pc, the first signs of the multiphase medium are spotted; however, at this low resolution thermal injection of feedback energy cannot yet create hot expanding bubbles around star-forming regions—instead feedback tends to erase high-density peaks and suppress SF. At l = 12 pc, we see the formation of cold (≲300 K), dense (≳100 M ☉ pc −3 ) clouds that maintain SF while being compressed by the hot medium; at the same time a large fraction of feedback energy is channeled into low-density bubbles and winds. These winds often entrain compact neutral clumps which produce multi-component metal absorption lines.
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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 | 0.001 |
| 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) | 0.001 | 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".