Distorted surfaces of magnetic helium-peculiar stars: an application to a Cen
Bibliographic record
Abstract
ABSTRACT Helium-peculiar magnetic chemically peculiar stars show variations of helium abundance across their surfaces. As a result of associated atmospheric scale height variations, the stellar surface becomes distorted, with helium-rich regions dented inwards. Effectively, on top of flux variations due to opacity effects, the depressed helium-rich surface regions become less bright in the optical regions and brighter in the ultraviolet. We study the observational effects of the aspherical surface on the light curves of a Cen. We simulate the light curves of this star adopting surface distributions of He, N, O, Si, and Fe derived from Doppler mapping and introducing the effect of distortion proportional to helium abundance. We show that while most of the optical and UV variations of this star result from flux redistribution due to the non-uniform surface distributions of helium and iron, the reduction of light variations due to the helium-related surface distortion leads to a better agreement between simulated optical light curves and the light curves observed with the BRITE satellites.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".