A super-Earth and a mini-Neptune near the 2:1 MMR straddling the radius valley around the nearby mid-M dwarf TOI-2096
Bibliographic record
Abstract
Context.Several planetary formation models have been proposed to explain the observed abundance and variety of compositions of super-Earths and mini-Neptunes. In this context, multitransiting systems orbiting low-mass stars whose planets are close to the radius valley are benchmark systems, which help to elucidate which formation model dominates. Aims.We report the discovery, validation, and initial characterization of one such system, TOI-2096 (TIC 142748283), a two-planet system composed of a super-Earth and a mini-Neptune hosted by a mid-type M dwarf located 48 pc away. Methods.We characterized the host star by combining optical spectra, analyzing its broadband spectral energy distribution, and using evolutionary models for low-mass stars. Then, we derived the planetary properties by modeling the photometric data from TESS and ground-based facilities. In addition, we used archival data, high-resolution imaging, and statistical validation to support our planetary interpretation. Results.We found that the stellar properties of TOI-2096 correspond to a dwarf star of spectral type M4±0.5. It harbors a super-Earth (R= 1.24 ± 0.07R⊕) and a mini-Neptune (R= 1.90 ± 0.09R⊕) in likely slightly eccentric orbits with orbital periods of 3.12 d and 6.39 d, respectively. These orbital periods are close to the first-order 2:1 mean-motion resonance (MMR), a configuration that may lead to measurable transit timing variations (TTVs). We computed the expected TTVs amplitude for each planet and found that they might be measurable with high-precision photometry delivering mid-transit times with accuracies of ≲2 min. Moreover, we conclude that measuring the planetary masses via radial velocities (RVs) could also be possible. Lastly, we found that these planets are among the best in their class to conduct atmospheric studies using the NIRSpec/Prism onboard theJames WebbSpace Telescope (JWST). Conclusions.The properties of this system make it a suitable candidate for further studies, particularly for mass determination using RVs and/or TTVs, decreasing the scarcity of systems that can be used to test planetary formation models around low-mass 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 | 0.000 | 0.000 |
| 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".