Investigating the spectroscopic, magnetic and circumstellar variability of the O9 subgiant star HD 57682
Bibliographic record
Abstract
The O9IV star HD 57682, discovered to be magnetic within the context of the Magnetism in Massive Stars (MiMeS) survey in 2009, is one of only eight convincingly detected magnetic O-type stars. Among this select group, it stands out due to its sharp-lined photospheric spectrum. Since its discovery, the MiMeS Collaboration has continued to obtain spectroscopic and magnetic observations in order to refine our knowledge of its magnetic field strength and geometry, rotational period and spectral properties and variability. In this paper we report new Echelle SpectroPolarimetric Device for the Observation of Stars (ESPaDOnS) spectropolarimetric observations of HD 57682, which are combined with previously published ESPaDOnS data and archival Hα spectroscopy. This data set is used to determine the rotational period (63.5708 ± 0.0057 d), refine the longitudinal magnetic field variation and magnetic geometry (dipole surface field strength of 880 ± 50 G and magnetic obliquity of 79° ± 4° as measured from the magnetic longitudinal field variations, assuming an inclination of 60°) and examine the phase variation of various lines. In particular, we demonstrate that the Hα equivalent width undergoes a double-wave variation during a single rotation of the star, consistent with the derived magnetic geometry. We group the variable lines into two classes: those that, like Hα, exhibit non-sinusoidal variability, often with multiple maxima during the rotation cycle, and those that vary essentially sinusoidally. Based on our modelling of the Hα emission, we show that the variability is consistent with emission being generated from an optically thick, flattened distribution of magnetically confined plasma that is roughly distributed about the magnetic equator. Finally, we discuss our findings in the magnetospheric framework proposed in our earlier study.
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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 | 0.000 |
| 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) | 0.000 | 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".