The impact of ultraviolet heating and cooling on the dynamics and observability of lava planet atmospheres
Bibliographic record
Abstract
Lava planets have non-global, condensible atmospheres similar to icy bodies within the solar system. Because they depend on interior dynamics, studying the atmospheres of lava planets can lead to understanding unique geological processes driven by their extreme environment. Models of lava planet atmospheres have thus far focused on either radiative transfer or hydrodynamics. In this study, we couple the two processes by introducing ultraviolet and infrared radiation to a turbulent boundary layer model. We also test the effect of different vertical temperature profiles on atmospheric dynamics. Results from the model show that UV radiation affects the atmosphere much more than IR. UV heating and cooling work together to produce a horizontally isothermal atmosphere away from the sub-stellar point regardless of the vertical temperature profile. We also find that stronger temperature inversions induce stronger winds and hence cool the atmosphere. Our simulated transmission spectra of the bound atmosphere show a strong SiO feature in the UV that would be challenging to observe in the planet's transit spectrum due to the precision required. Our simulated emission spectra are more promising, with significant SiO spectral features at 4.5 and 9 $\mu$m that can be observed with the James Webb Space Telescope. Different vertical temperature profiles produce discernible dayside emission spectra, but not in the way one would expect.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".