Quantifying thermal water dissociation in the dayside photosphere of WASP-121 b using NIRPS
Bibliographic record
Abstract
The intense stellar irradiation of ultra-hot Jupiters results in some of the most extreme atmospheric environments in the planetary regime. On their daysides, temperatures can be sufficiently high for key atmospheric constituents to thermally dissociate into simpler molecular species and atoms. This dissociation drastically changes the atmospheric opacities and, in turn, critically alters the temperature structure, atmospheric dynamics, and day-night heat transport. To date, however, simultaneous detections of the dissociating species and their thermally dissociation products in exoplanet atmospheres have remained rare. In this work we present the simultaneous detections of H2O and its thermally dissociation product OH on the dayside of the ultra-hot Jupiter WASP-121 b based on high-resolution emission spectroscopy with the recently commissioned Near InfraRed Planet Searcher (NIRPS). We retrieved a photospheric abundance ratio of log10(OH/H2O) = −0.15 ± 0.20, indicating that there is about as much OH as H2O at photospheric pressures, which confirms predictions from chemical equilibrium models. We compared the dissociation on WASP-121 b with other ultra-hot Jupiters and show that a trend in agreement with equilibrium models arises. We also discuss an apparent velocity shift of 4.79−0.97+0.93 km s−1 in the H2O signal, which is not reproduced by current global circulation models. Finally, in addition to H2O and OH, the NIRPS data reveal evidence of Fe and Mg, from which we inferred a Fe/Mg ratio consistent with the solar and host star ratios. Our results demonstrate that NIRPS can be an excellent instrument to obtain simultaneous measurements of refractory and volatile molecular species, thus paving the way for many future studies on the atmospheric composition, chemistry, and the formation history of close-in exoplanets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".