Partial Paschen-Back splitting of Si <scp>ii</scp> and Si <scp>iii</scp> lines in magnetic CP stars
Bibliographic record
Abstract
Abstract A number of prominent spectral lines in the spectra of magnetic A and B main sequence stars are produced by closely spaced doublets or triplets. Depending on the strength and orientation of magnetic field, the PPB magnetic splitting can result in the Stokes I profiles of a spectral line that differ significantly from those predicted by the theory of Zeeman effect. Such lines should be treated using the theory of the partial Paschen-Back (PPB) effect. To estimate the error introduced by the use of the Zeeman approximation, numerical simulations have been performed for Si ii and Si iii lines assuming an oblique rotator model. The analysis indicates that for high precision studies of some spectral lines the PPB approach should be used if the field strength at the magnetic poles is Bp > 6-10 kG and V sin i < 15 km s−1. In the case of the Si ii line 5041 Å, the difference between the simulated PPB and Zeeman profiles is caused by a significant contribution from a so called “ghost” line. The Stokes I and V profiles of this particular line simulated in the PPB regime provide a significantly better fit to the observed profiles in the spectrum of the magnetic Ap star HD 318107 than the profiles calculated assuming the Zeeman effect.
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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 | 0.000 | 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 | 0.000 |
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".