Into the storm: diving into the winds of the ultra-hot Jupiter WASP-76 b with HARPS and ESPRESSO
Bibliographic record
Abstract
Context. Despite swift progress in the characterisation of exoplanet atmospheres in composition and structure, the study of atmospheric dynamics has not progressed at the same speed. While theoretical models have been developed to describe the lower layers of the atmosphere, and independently, the exosphere, little is known about the intermediate layers up to the thermosphere. Aims. We aim to provide a clearer picture of atmospheric dynamics for the class of ultra-hot Jupiters, which are highly irradiated gas giants, based on the example of WASP-76 b. Methods. We jointly analysed two datasets that were obtained with the HARPS and ESPRESSO spectrographs to interpret the resolved planetary sodium doublet. We then applied the MERC code, which retrieves wind patterns, speeds, and temperature profiles on the line shape of the sodium doublet. An updated version of MERC, with added planetary rotation, also provides the possibility of modelling the latitude dependence of the wind patterns. Results. We retrieve the highest Bayesian evidence for an isothermal atmosphere, interpreted as a mean temperature of 3389 ± 227 K, a uniform day- to nightside wind of 5.5−2.0+1.4 km s−1 in the lower atmosphere with a vertical wind in the upper atmosphere of 22.7−4.1+4.9 km s−1, switching atmospheric wind patterns at 10−3 bar above the reference surface pressure (10 bar). Conclusions. Our results for WASP-76 b are compatible with previous studies of the lower atmospheric dynamics of WASP-76 b and other ultra-hot Jupiters. They highlight the need for vertical winds in the intermediate atmosphere above the layers probed by global circulation model studies to explain the line broadening of the sodium doublet in this planet. This work demonstrates the capability of exploiting the resolved spectral line shapes to observationally constrain possible wind patterns in exoplanet atmospheres. This is an invaluable input to more sophisticated 3D atmospheric models in the future.
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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 | 0.001 | 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 | 0.001 |
| 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".