Extreme cloud collisions in nearby barred galaxies
Bibliographic record
Abstract
ABSTRACT The inner regions of the Milky Way are known to contain an enigmatic population of prominent molecular clouds characterized by extremely broad lines. The physical origin of these ‘extended velocity features’ (EVFs) is still debated, although a connection with the ‘dust lanes’ of the Galactic bar has been hypothesized. In this paper, we search for analogous features in the dust lanes of nearby barred galaxies using the PHANGS–ALMA CO(2-1) survey. We aim to confirm existence of EVFs in other galaxies and to take advantage of the external perspective to gain insight into their origin. We study a sample of 29 barred galaxies and find that 34 per cent contain one or more EVFs, while the remaining lack obvious signs of EVFs. Upon analysing the physical properties of the EVFs, we find they possess large virial parameters, ranging from few hundreds to several thousand, indicating that they are strongly out-of-equilibrium. The most likely explanation for their origin is extreme cloud–cloud collisions with relative velocities in excess of 100 km s−1 in highly non-circular flow driven by the bar. This interpretation is consistent with previous high-resolution observations in Milky Way. Further corroboration of this interpretation comes from the inspection of high-sensitivity infrared observations from the PHANGS–JWST Treasury Survey that reveals streams of gas that appear to be hitting the dust lanes at locations where EVFs are found. We argue that EVFs are the clearest examples of cloud–cloud collisions available in literature and represent a unique opportunity to study cloud collisions and their impact on star formation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".