Deep Two-phase, Hemispherical Magma Oceans on Lava Planets
Bibliographic record
Abstract
Abstract Astronomers have discovered a handful of exoplanets with rocky bulk compositions but orbiting that orbit so close to their host star that the surface of the planet must be at least partially molten. It is expected that the dayside of such “lava planets” harbors a rock-vapor atmosphere that flows quickly toward the airless nightside—this partial atmosphere is critical to the interpretation of lava planet observations, but transports negligible heat toward the nightside. As a result, the surface temperature of the magma ocean may range from 3000 K near the substellar point down to 1500 K near the day–night terminator. We use simple models incorporating the thermodynamics and geochemistry of partial melt to predict the physical and chemical properties of the magma ocean as a function of the distance from the substellar point. Our principal findings are that: (1) the dayside magma ocean is much deeper than previously thought, probably extending down to the core–mantle boundary below the substellar point of an Earth-sized planet; (2) much of the dayside is only partially molten, leading to gradients in the surface chemistry of the magma ocean; and (3) the temperature at the base of the silicate mantle is as important as the surface temperature. In the most extreme cases, lava planet interiors could be cold enough such that thermal stratification below the substellar point is gravitationally stable. These findings have important implications for the dynamics of the magma ocean, as well as the composition and dynamics of the atmosphere.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".