From theory to observation: Understanding filamentary flows in high-mass star-forming clusters
Bibliographic record
Abstract
Context. Filamentary structures on parsec scales play a critical role in feeding star-forming regions, where they often act as the main channels through which gas flows into dense clumps that foster star formation. It is crucial to understand the dynamics of these filaments to explain the mechanisms of star formation in a range of environments. Aims. We used data from multi-scale galactic magnetohydrodynamics simulations to observe filaments and star-forming clumps on dozens of parsec scales and investigate flow rate relations along and onto filaments as well as flows towards the clumps. Methods. Using the FilFinderPPV identification technique, we identified the prominent filamentary structures in each data cube. Each filament and its corresponding clump were analysed by calculating the flow rates along each filament towards the clump, onto each filament from increasing distances, and radially around each clump. This analysis was conducted for two cubes, one feedback-dominated region, and one cube with less feedback, as well as for five different inclinations (0, 20, 45, 70, and 90 degrees) of one filament and clump system. Results. The face-on inclination of the simulations (0 degrees) shows different trends depending on the environmental conditions (more or less feedback). The median flow rate in the region with more feedback is 8.9 × 10−5 M⊙yr−1, and the flow rates along the filaments towards the clumps generally decrease in these regions. In the region with less feedback, the median flow rate is 2.9 × 10−4 M⊙yr−1 and along the filaments, the values either increase or remain constant. The order of magnitude of the flow rates from the environments onto the primary filaments suffices to sustain the flow rates along these filaments. The effects of galactic and filamentary inclination also show that when the filaments are viewed from different galactic inclinations, feeder structures become clear (smaller filamentary structures that aid in the flow of material). Additionally, considering the inclination of the filaments themselves allowed us to determine by how much we over- or underestimated the flow rates for these filaments. Conclusions. The different trends in the relation between flow rate and distance along the filaments in the feedback and non-feedback dominated cubes confirm that the environment is a significant factor in accretion flows and their relation with the filament parameters. The method we used to estimate these flow rates, which was previously applied to observational data, produced results that are consistent with those obtained from the simulations themselves. We are therefore very confident in the flow-rate calculation method.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".