Measuring small-scale magnetic fields of 44 M dwarfs from SPIRou spectra with <tt>ZeeTurbo</tt>
Bibliographic record
Abstract
ABSTRACT We present the results of an analysis aimed at probing the small-scale magnetic fields of M dwarfs observed with SPIRou, the nIR high-resolution spectro-polarimeter installed at the Canada–France–Hawaii Telescope, in the context of the SPIRou Legacy Survey. Our analysis relies on high-resolution median spectra built from several tens of spectra recorded between 2019 and 2022, and on synthetic spectra computed with the ZeeTurbo code for various combination of atmospheric parameters and magnetic field strengths. We pursue the efforts undertaken in a previous study and focus on 44 weakly to moderately active M dwarfs. We derive average magnetic field strengths () ranging from 0.05 to 1.15 kG, in good agreement with activity estimates and rotation periods. We found that including magnetic fields in our models has virtually no impact on our derived atmospheric parameters, and that a priori assumptions on the stellar surface gravity can affect our estimated . Our results suggest that small-scale magnetic fields account for more than 70 per cent of the overall average magnetic field for most targets whose large-scale fields were previously measured. We derived low magnetic fluxes for several targets in our sample, and found no clear evidence that decreases with increasing Rossby number in the unsaturated dynamo regime. We even identified counterexamples (GJ 1289 and GJ 1286) where the small-scale field is unusually strong despite the long rotation period. Along with similar results on the large-scale fields, our findings further suggest that dynamo processes may operate in a non-conventional mode in these strongly magnetic, slowly rotating stars.
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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 | 0.001 |
| 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".