Detecting Magnetic Fields in Rotationally Perturbed, Hot Stellar Winds
Bibliographic record
Abstract
In this paper, we report on an attempt to optically detect localized and/or variable magnetic fields in the single O4 I(n)f star ζ Puppis and in the WC 8 star in the binary star γ 2 Velorum with the spectropolarimeter Cassegrain echelle spectrograph mounted on the ESO 3.6 m telescope. The spectra cover 5700–6800 Å with resolution element 0.2 Å. These stars are sufficiently bright in principle to obtain Stokes V spectra with excellent signal‐to‐noise ratio and temporal resolution at this telescope. We discuss several procedures adapted to the extraction of the polarized signal from broad lines to put constraints on the global and local magnetic fields. Despite some instrumental difficulties, we report a null longitudinal component of the global magnetic field measurement in ζ Pup with σ B l ∼200 G. We also find no significant activity in Stokes V above 3σ V ∼0.3% in 10 minutes in ζ Puppis's observable photospheric lines, in a spectral bandpass of 0.2–3 Å. We also report a null detection above 3σ V ∼0.3% for the emission lines of γ Vel. Spectral variability in natural light for these stars is also discussed. Finally, we discuss the potential of such spectropolarimetric techniques in the context of new‐generation spectropolarimeters.
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 | 0.000 |
| 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".