Testing the Origin of Hot Jupiters with Atmospheric Surveys
Bibliographic record
Abstract
Abstract In spite of their long detection history, the origin of hot Jupiters remains to be resolved. While dynamical evidence suggests high-eccentricity migration is most likely, conflicts remain when considering hot Jupiters as a population in the context of warm and cold Jupiters. Here, we turn to atmospheric signatures as an alternative means to test the origin theory of hot Jupiters, focusing on population level trends that arise from post-formation pollution, motivated by the upcoming Ariel space mission whose goal is to deliver a uniform sample of exoplanet atmospheric constraints. We experiment with post-formation pollution by planetesimal accretion, pebble accretion, and disk-induced migration and find that an observable signature of post-formation pollution is only possible under pebble accretion in metal-heavy disks. If most hot Jupiters arrive at their present orbit by high-eccentricity migration while warm Jupiters emerge largely in situ, we expect the atmospheric water abundance of hot Jupiters to be significantly elevated compared to warm Jupiters. We report on the detectability of such signatures and further provide suggestions for future comparative atmospheric characterization between hot Jupiters and wide-orbit directly imaged planets to elucidate the properties of the dust substructures in protoplanetary disks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".