The magnetic field and stellar wind of the mature late-F star χ Draconis A
Bibliographic record
Abstract
ABSTRACT F stars lie in the transition region between cool stars with dynamo generated fields and hot star fossil fields and offer an interesting window into the generation of magnetic fields in shallow convection zones. In this paper, we investigate the magnetic field of the mature F7V primary of the bright χ Draconis system. χ Dra was observed in circularly polarized light at four epochs from 2014 through to 2019 using the NARVAL spectropolarimeter at the Téléscope Bernard Lyot. Using the technique of least-squares deconvolution, we created high signal-to-noise line profiles from which we were able to measure the radial velocity of both the primary and secondary and use these to improve the orbital parameters of the system. Additionally, we used the technique of Zeeman Doppler imaging to reconstruct the large-scale magnetic field geometry of the primary at the four epochs. The magnetic maps show that χ Dra A has a predominately dipolar poloidal magnetic field at all epochs with the magnetic axis well aligned with the stellar rotation axis. The large-scale features of the magnetic field appear to be relatively stable over the ∼5 yr time base of our observations, with no evidence of any polarity reversals. We used the magnetic field maps to model the wind from χ Dra A at all epochs, showing that the mass-loss from the stellar wind of χ Dra A is 3–6 times the current solar value, while the angular momentum loss from the wind is around 3–4 times the solar value.
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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) | 0.001 | 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".