From Pretransit to Posteclipse: Investigating the Impact of 3D Temperature, Chemistry, and Dynamics on High-resolution Emission Spectra of the Ultrahot Jupiter WASP-76b
Bibliographic record
Abstract
Abstract High-resolution spectroscopy has provided a wealth of information about the climate and composition of ultrahot Jupiters (UHJs). However, the 3D structure of their atmospheres makes observations more challenging to interpret, necessitating 3D forward-modeling studies. In this work, we model phase-dependent thermal emission spectra of the archetype UHJ WASP-76b to understand how the line strengths and Doppler shifts of Fe, CO, H2O, and OH evolve throughout the orbit. We postprocess outputs of the SPARC/MITgcm global circulation model with the 3D Monte Carlo radiative transfer code gCMCRT to simulate emission spectra at 36 orbital phases. We then cross correlate the spectra with different templates to obtain cross-correlation function and K p–V sys maps. For each species, our models produce consistently negative K p offsets in pre- and posteclipse, which are driven by planet rotation. The size of these offsets is similar to the equatorial rotation velocity of the planet. Furthermore, we demonstrate how the weak vertical temperature gradient on the nightside of UHJs mutes the absorption features of CO and H2O, which significantly hampers their detectability in pre- and posttransit. We also show that the K p and V sys offsets in pre- and posttransit are not always a measure of the line-of-sight velocities in the atmosphere. This is because the cross-correlation signal is a blend of dayside emission and nightside absorption features. Finally, we highlight that the observational uncertainty in the known orbital velocity of UHJs can be multiple kilometers per second, which makes it hard for certain targets to meaningfully report absolute K p offsets.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".