Sculpting the Sub-Saturn Occurrence Rate via Atmospheric Mass Loss
Bibliographic record
Abstract
Abstract The sub-Saturn (∼4–8 R ⊕) occurrence rate rises with orbital period out to at least ∼300 days. In this work we adopt and test the hypothesis that the decrease in their occurrence toward the star is a result of atmospheric mass loss, which can transform sub-Saturns into sub-Neptunes (≲4 R ⊕) more efficiently at shorter periods. We show that under the mass-loss hypothesis, the sub-Saturn occurrence rate can be leveraged to infer their underlying core mass function, and, by extension, that of gas giants. We determine that lognormal core mass functions peaked near ∼10–20 M ⊕ are compatible with the sub-Saturn period distribution, the distribution of observationally inferred sub-Saturn cores, and gas-accretion theories. Our theory predicts that close-in sub-Saturns should be ∼50% less common and ∼30% more massive around rapidly rotating stars; this should be directly testable for stars younger than ≲500 Myr. We also predict that the sub-Jovian desert becomes less pronounced and opens up at smaller orbital periods around M stars compared to solar-type stars (∼0.7 days versus ∼3 days). We demonstrate that exceptionally low-density sub-Saturns, “super-puffs,” can survive intense hydrodynamic escape to the present day if they are born with even larger atmospheres than they currently harbor; in this picture, Kepler 223 d began with an envelope ∼1.5× the mass of its core and is currently losing its envelope at a rate of ∼2 × 10−3 M ⊕ Myr−1. If the predictions from our theory are confirmed by observations, the core mass function we predict can also serve to constrain core formation theories of gas-rich planets.
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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 | 0.002 |
| 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 | 0.000 |
| 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".