WATER ICE LINES AND THE FORMATION OF GIANT MOONS AROUND SUPER-JOVIAN PLANETS
Bibliographic record
Abstract
Most of the exoplanets with known masses at Earth-like distances to Sun-like stars are heavier than Jupiter, which raises the question of whether such planets are accompanied by detectable, possibly habitable moons. Here we simulate the accretion disks around super-Jovian planets and find that giant moons with masses similar to Mars can form. Our results suggest that the Galilean moons formed during the final stages of accretion onto Jupiter, when the circumjovian disk was sufficiently cool. In contrast to other studies, with our assumptions, we show that Jupiter was still feeding from the circumsolar disk and that its principal moons cannot have formed after the complete photoevaporation of the circumsolar nebula. To counteract the steady loss of moons into the planet due to type I migration, we propose that the water ice line around Jupiter and super-Jovian exoplanets acted as a migration trap for moons. Heat transitions, however, cross the disk during the gap opening within ≈10 4 years, which makes them inefficient as moon traps and indicates a fundamental difference between planet and moon formation. We find that icy moons larger than the smallest known exoplanet can form at about 15–30 Jupiter radii around super-Jovian planets. Their size implies detectability by the Kepler and PLATO space telescopes as well as by the European Extremely Large Telescope. Observations of such giant exomoons would be a novel gateway to understanding planet formation, as moons carry information about the accretion history of their planets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".