On filament fragmentation and the impact of ambient environment on it
Bibliographic record
Abstract
ABSTRACT Filaments are crucial intermediaries in the star formation process. Recent observations of filaments show that (i) a number of them are non-singular entities, and rather a bundle of velocity coherent fibres, and (ii) while a majority of filaments spawn cores narrower than their natal filaments, some cores are broader. We explore these issues by developing hydrodynamic simulations of an initially sub-critical individual filament that is allowed to accrete gas from its neighbourhood and evolves under self-gravity. Results obtained here support the idea that fibres form naturally during the filament formation process. We further argue that the ambient environment, i.e. the magnitude of external pressure, and not the filament linemass alone, has bearing upon the morphology of its evolution. We observe that a filament is susceptible to the sausage-type instability irrespective of the external pressure. The fragments, however, are pinched in a filament experiencing pressure comparable to that in the Solar neighbourhood (∼104 K cm−3). By contrast, fragments are broad and spherical – having density profiles similar to that of a stable Bonnor–Ebert sphere – when the filament experiences a higher pressure, typically ≥105 K cm−3, but ≤106 K cm−3). The filament tends to rupture at even higher external pressure (≥107 K cm−3). These observations collectively mean that star formation is less efficient with increasing external pressure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".