CO or no CO? Narrowing the CO abundance constraint and recovering the H2O detection in the atmosphere of WASP-127 b using SPIRou
Bibliographic record
Abstract
Precise measurements of chemical abundances in planetary atmospheres are necessary to constrain the formation histories of exoplanets. A recent study of WASP-127b, a close-in puffy sub-Saturn orbiting its solar-type host star in 4.2 d, using HST and Spitzer revealed a feature-rich transmission spectrum with strong excess absorption at 4.5 um. However, the limited spectral resolution and coverage of these instruments could not distinguish between CO and/or CO2 absorption causing this signal, with both low and high C/O ratio scenarios being possible. Here we present near-infrared (0.9--2.5 um) transit observations of WASP-127 b using the high-resolution SPIRou spectrograph, with the goal to disentangle CO from CO2 through the 2.3 um CO band. With SPIRou, we detect H2O at a t-test significance of 5.3 sigma and observe a tentative (3 sigma) signal consistent with OH absorption. From a joint SPIRou + HST + Spitzer retrieval analysis, we rule out a CO-rich scenario by placing an upper limit on the CO abundance of log10[CO]<-4.0, and estimate a log10[CO2] of -3.7^(+0.8)_(-0.6), which is the level needed to match the excess absorption seen at 4.5um. We also set abundance constraints on other major C-, O-, and N-bearing molecules, with our results favoring low C/O (0.10^(+0.10)_(-0.06)), disequilibrium chemistry scenarios. We further discuss the implications of our results in the context of planet formation. Additional observations at high and low-resolution will be needed to confirm these results and better our understanding of this unusual world.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".