About 30% of Sun-like Stars Have Kepler-like Planetary Systems: A Study of Their Intrinsic Architecture
Bibliographic record
Abstract
Abstract We constrain the intrinsic architecture of Kepler planetary systems by modeling the observed multiplicities of the transiting planets (tranets) and their transit timing variations (TTVs). We robustly determine that the fraction of Sun-like stars with Kepler -like planets, η Kepler , is 30 ± 3%. Here, Kepler -like planets are planets that have radii R p ≳ R ⊕ and orbital periods P < 400 days. Our result thus significantly revises previous claims that more than 50% of Sun-like stars have such planets. Combined with the average number of Kepler planets per star (∼0.9), we obtain that on average each planetary system has 3.0 ± 0.3 planets within 400 days. We also find that the dispersion in orbital inclinations of planets within a given planetary system, σ i , k , is a steep function of its number of planets, k . This can be parameterized as and we find that −4 < α < −2 at the 2 σ level. Such a distribution well describes the observed multiplicities of both transits and TTVs with no excess of single-tranet systems. Therefore we do not find evidence supporting the so-called “ Kepler dichotomy.” Together with a previous study on orbital eccentricities, we now have a consistent picture: the fewer planets in a system, the hotter it is dynamically. We discuss briefly possible scenarios that lead to such a trend. Despite our solar system not belonging to the Kepler club, it is interesting to notice that the solar system also has three planets within 400 days and that the inclination dispersion is similar to Kepler systems of the same multiplicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".