Stokes IQUV magnetic Doppler imaging of Ap stars – II. Next generation magnetic Doppler imaging of α2 CVn★
Bibliographic record
Abstract
We present updated magnetic field maps of the chemically peculiar B9p star α2 CVn created using a series of time-resolved observations obtained using the high-resolution spectropolarimeters ESPaDOnS and Narval. We compare these new magnetic field maps with the original magnetic Doppler imaging maps based on spectra recorded with the MuSiCoS spectropolarimeter and taken a decade earlier. These new maps are inferred from line profiles in all four Stokes parameters using the magnetic Doppler imaging code invers10. With the addition of new lines exhibiting Stokes IQUV signatures, we have a unique insight into how the derived magnetic surface structure may be affected by the atomic lines chosen for inversion. We report new magnetic maps of α2 CVn created using strong iron lines (directly comparable to the published MuSiCoS maps), weak iron lines and chromium lines, all of which yield a magnetic field structure roughly consistent with that obtained previously. We then derive an updated magnetic structure map for α2 CVn based on the complete sample of Fe and Cr lines, which we believe to produce a more representative model of the magnetic topology of α2 CVn. In agreement with the previous mapping, this new updated magnetic map shows a dipolar-like field which has complex sub-structure which cannot be explained by a simple low-order multipolar geometry. Our new maps show that regardless of the atomic line or species choice, the reconstructed magnetic field is consistent with that published previously, suggesting that the reconstructed field is a realistic representation of the magnetic field of α2 CVn. α2 CVn is the first Ap star for which multiple, high-resolution magnetic maps have been derived, providing important observational evidence for the stability of both the large- and small-scale magnetic field.
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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 | 0.001 |
| 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".