Heavy-element-enriched atmospheres and where they are born
Bibliographic record
Abstract
The heavy element content of giant exoplanets, inferred from structure models based on their radius and mass, often exceeds predictions based on classical core accretion. Pebble drift, coupled with volatile evaporation, has been proposed as a possible remedy to this since the level of heavy element enrichment a planet can accrete, as well as its atmospheric composition, is strongly dependent on where in the disc it is forming. We used a planet formation model that simulates the evolution of the protoplanetary disc, accounting for pebble growth, drift and evaporation, and the formation of planets from pebble and gas accretion. We simulated the growth and migration of planetary embryos in ten different protoplanetary discs whose chemical compositions are matched to the host stars of the planets that we aim to reproduce; this provided a more realistic model of their growth than previous studies. The heavy element content of giant exoplanets was used to infer their formation location and thus to estimate their atmospheric abundances. We focused on giants more massive than Saturn, as we expect that their heavy element content is dominated by their envelope rather than their core. The heavy element content of nine out of the ten simulated planets is successfully matched to their observed values. Our simulations predict formation in the inner disc regions, where the majority of the volatiles have already evaporated and can thus be accreted onto the planet via the gas. As the majority of the planetary heavy element content originates from water vapour accretion, our simulations predict a high atmospheric O/H ratio in combination with a low atmospheric C/O ratio, which is in general agreement with observations. For certain planets, namely WASP-84b, these properties may be observable in the near future, offering a method of testing the constraints placed on the planet’s formation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".