Magnetic field topologies of the bright, weak-field Ap stars θ Aurigae and
Bibliographic record
Abstract
Context. The brightest magnetic chemically peculiar stars θ Aur and ε UMa were targeted by numerous studies of their photometric and spectroscopic variability. Detailed maps of chemical abundance spots were repeatedly derived for both stars. However, owing to the weakness of their surface magnetic fields, very little information on the magnetic field geometries of these stars is available. Aims. In this study we aim to determine detailed magnetic field topologies of θ Aur and ε UMa based on modern, high-resolution spectropolarimetric observations. Methods. Both targets were observed in all four Stokes parameters using the Narval and ESPaDOnS spectropolarimeters. A multi-line technique of least-squares deconvolution was employed to detect polarisation signatures in spectral lines. These signatures were modelled with a Zeeman-Doppler imaging code. Results. We succeed in detecting variable circular and linear polarisation signatures for θ Aur. Only circular polarisation was detected for ε UMa. We obtain new sets of high-precision longitudinal magnetic field measurements using mean circular polarisation metal line profiles as well as hydrogen line cores, which are consistent with historical data. Magnetic inversions revealed distorted dipolar geometries in both stars. The Fe and Cr abundance distributions, reconstructed simultaneously with magnetic mapping, do not show a clear correlation with the local magnetic field properties, with the exception of a relative element underabundance in the horizontal field regions along the magnetic equators. Conclusions. Our study provides the first ever detailed surface magnetic field maps for broad-line, weak-field chemically peculiar stars, showing that their field topologies are qualitatively similar to those found in stronger field stars. The Fe and Cr chemical abundance maps reconstructed for θ Aur and ε UMa are at odds with the predictions of current theoretical atomic diffusion calculations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".