A high-resolution spectropolarimetric survey of Herbig Ae/Be stars★ – II. Rotation
Bibliographic record
Abstract
We report the analysis of the rotational properties of our sample of Herbig Ae/Be (HAeBe) and related stars for which we have obtained high-resolution spectropolarimetric observations. Using the projected rotational velocities measured at the surface of the stars, we have calculated the angular momentum of the sample and plotted it as a function of age. We have then compared the angular momentum and the v sin i distributions of the magnetic to the non-magnetic HAeBe stars. Finally, we have predicted v sin i of the non-magnetic, non-binary (‘normal’) stars in our sample when they reach the zero-age main sequence (ZAMS), and compared them to various catalogues of v sin i of main-sequence stars. First, we observe that magnetic HAeBe stars are much slower rotators than normal stars, indicating that they have been more efficiently braked than the normal stars. In fact, the magnetic stars have already lost most of their angular momentum, despite their young ages (lower than 1 Myr for some of them). Secondly, our analysis suggests that the low-mass (1.5 < M < 5 M⊙) normal HAeBe stars evolve with constant angular momentum towards the ZAMS, while the high-mass normal HAeBe stars (M > 5 M⊙) are losing angular momentum. We propose that winds, which are expected to be stronger in massive stars, are at the origin of this phenomenon.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".