A hot Jupiter around the very active weak-line T Tauri star TAP 26
Bibliographic record
Abstract
We report the results of an extended spectropolarimetric and photometric monitoring of the weak-line T Tauri star TAP 26, carried out within the Magnetic Topologies of Young Stars and the Survival of close-in massive Exoplanets (MaTYSSE) programme with the Echelle SpectroPolarimetric Device for the Observation of Stars (ESPaDOnS) spectropolarimeter at the 3.6-m Canada–France–Hawaii Telescope. Applying Zeeman–Doppler Imaging (ZDI) to our observations, concentrating in 2015 November and 2016 January and spanning 72 d in total, 16 d in 2015 November and 13 d in 2016 January, we reconstruct surface brightness and magnetic field maps for both epochs and demonstrate that both distributions exhibit temporal evolution not explained by differential rotation alone. We report the detection of a hot Jupiter (hJ) around TAP 26 using three different methods, two using ZDI and one Gaussian-process regression (GPR), with a false-alarm probability smaller than 6 × 10−4. However, as a result of the aliasing related to the observing window, the orbital period cannot be uniquely determined; the orbital period with highest likelihood is 10.79 ± 0.14 d followed by 8.99 ± 0.09 d. Assuming the most likely period, and that the planet orbits in the stellar equatorial plane, we obtain that the planet has a minimum mass Msin i of 1.66 ± 0.31 MJup and orbits at 0.0968 ± 0.0032 au from its host star. This new detection suggests that disc type II migration is efficient at generating newborn hJs, and that hJs may be more frequent around young T Tauri stars than around mature stars (or that the MaTYSSE sample is biased towards hJ-hosting 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 | 0.000 |
| 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".