TOI-1759 b: A transiting sub-Neptune around a low mass star characterized with SPIRou and TESS
Bibliographic record
Abstract
We report the detection and characterization of the transiting sub-Neptune TOI-1759 b, using photometric time-series from TESS and near infrared spectropolarimetric data from SPIRou on the CFHT. TOI-1759 b orbits a moderately active M0V star with an orbital period of $18.849975\pm0.000006$ d, and we measure a planetary radius and mass of $3.06\pm0.22$ R$_\oplus$ and $6.8\pm2.0$ M$_\oplus$. Radial velocities were extracted from the SPIRou spectra using both the CCF and the LBL methods, optimizing the velocity measurements in the near infrared domain. We analyzed the broadband SED of the star and the high-resolution SPIRou spectra to constrain the stellar parameters and thus improve the accuracy of the derived planet parameters. A LSD analysis of the SPIRou Stokes $V$ polarized spectra detects Zeeman signatures in TOI-1759. We model the rotational modulation of the magnetic stellar activity using a GP regression with a quasi-periodic covariance function, and find a rotation period of $35.65^{+0.17}_{-0.15}$ d. We reconstruct the large-scale surface magnetic field of the star using ZDI, which gives a predominantly poloidal field with a mean strength of $18\pm4$ G. Finally, we perform a joint Bayesian MCMC analysis of the TESS photometry and SPIRou RVs to optimally constrain the system parameters. At $0.1176\pm0.0013$ au from the star, the planet receives $6.4$ times the bolometric flux incident on Earth, and its equilibrium temperature is estimated at $433\pm14$ K. TOI-1759 b is a likely gas-dominated sub-Neptune with an expected high rate of photoevaporation. Therefore, it is an interesting target to search for neutral hydrogen escape, which may provide important constraints on the planetary formation mechanisms responsible for the observed sub-Neptune radius desert.
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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 | 0.001 | 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".