Investigating the young AU Mic system with SPIRou: large-scale stellar magnetic field and close-in planet mass
Bibliographic record
Abstract
ABSTRACT We present a velocimetric and spectropolarimetric analysis of 27 observations of the 22-Myr M1 star AU Microscopii (AU Mic) collected with the high-resolution YJHK (0.98–2.35 μm) spectropolarimeter SPIRou from 2019 September 18 to November 14. Our radial velocity (RV) time-series exhibits activity-induced fluctuations of 45 m s−1 rms, ∼3 times smaller than those measured in the optical domain, that we filter using Gaussian Process Regression. We report a 3.9σ detection of the recently discovered 8.46 -d transiting planet AU Mic b, with an estimated mass of 17.1$^{+4.7}_{-4.5}$ M⊕ and a bulk density of 1.3 ± 0.4 g cm−3, inducing an RV signature of semi-amplitude K = 8.5$^{+2.3}_{-2.2}$ m s−1 in the spectrum of its host star. A consistent detection is independently obtained when we simultaneously image stellar surface inhomogeneities and estimate the planet parameters with Zeeman–Doppler imaging (ZDI). Using ZDI, we invert the time-series of unpolarized and circularly polarized spectra into surface brightness and large-scale magnetic maps. We find a mainly poloidal and axisymmetric field of 475 G, featuring, in particular, a dipole of 450 G tilted at 19° to the rotation axis. Moreover, we detect a strong differential rotation of dΩ = 0.167 ± 0.009 rad d−1 shearing the large-scale field, about twice stronger than that shearing the brightness distribution, suggesting that both observables probe different layers of the convective zone. Even though we caution that more RV measurements are needed to accurately pin down the planet mass, AU Mic b already appears as a prime target for constraining planet formation models, studying the interactions with the surrounding debris disc, and characterizing its atmosphere with upcoming space- and ground-based missions.
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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 | 0.001 |
| 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".