Angular momentum loss rates in Be stars determined by the viscous decretion disc model
Bibliographic record
Abstract
ABSTRACT Circumstellar discs around Be stars are formed by the material ejected by the central star. This process removes excess angular momentum from the star as viscosity facilitates the mass and angular momentum transfer within the disc and its growth. The angular momentum loss rates (AMLR) of Be stars is a subject of debate in the literature. Through the modelling of the disc formation and dissipation phases observed from Be stars, their average AMLR can be determined and this is the goal of this work. We use the viscous decretion disc (VDD) model to provide a range of the average AMLR for Be stars and compare these rates with predicted values from the literature. We explore the reasons for discrepancies between the predicted values of average AMLR, using the VDD and Geneva stellar evolution models that were previously reported in literature and find that the largest differences occur when Be stars are rotating below their critical speeds. We show that the time over which the mass reservoir builds up is inversely proportional to the average AMLR. Also, we determine a revised value of the average AMLR for the Galactic Be star ω CMa of $4.7\times 10^{36}\, \mathrm{g\, cm^2\, s^{-2}}$, which is in better agreement with the values expected for a typical B2-type star. Finally, the effect of disc truncation due to the presence of a companion star is investigated and we find that this has a minimal effect on the average AMLR.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".