Variability from Thermoresistive Instability in the Atmospheres of Hot Jupiters
Bibliographic record
Abstract
Abstract The atmosphere of a hot Jupiter may be subject to a thermoresistive instability, in which the increasing electrical conductivity with temperature leads to runaway ohmic heating. We introduce a simplified model of the local dynamics in the equatorial region of a hot Jupiter that incorporates the back reaction on the atmospheric flow as the increasing electrical conductivity leads to flux freezing, which in turn quenches the flow and therefore the ohmic heating. We demonstrate a new time-dependent solution that emerges for a temperature-dependent electrical conductivity (whereas a temperature-independent conductivity always evolves to a steady state). The periodic cycle consists of bursts of Alfvén oscillations separated by quiescent intervals, with the magnetic Reynolds number alternating between values smaller than and larger than unity, maintaining the oscillation. We investigate the regions of pressure and temperature in which the instability operates. For the typical equatorial accelerations seen in atmospheric models, we find instability at pressures ∼0.1–1 bar and temperatures ≈1300–1800 K for magnetic fields ∼10 G. Unlike previous studies based on a constant wind velocity, we find that the instability is stronger for weaker magnetic fields. Our results add support to the idea that variability should be a feature of magnetized hot Jupiter atmospheres, particularly at intermediate temperatures. The temperature dependence of the electrical conductivity is an important ingredient that should be included in MHD models of hot Jupiter atmospheric dynamics.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".