Muted Features in the JWST NIRISS Transmission Spectrum of Hot Neptune LTT 9779b
Bibliographic record
Abstract
Abstract The hot Neptune desert is one of the most sparsely populated regions of the exoplanet parameter space, and atmosphere observations of its few residents can provide insights into how such planets have managed to survive in such an inhospitable environment. Here, we present transmission observations of LTT 9779 b, the only known hot Neptune to have retained a significant H/He-dominated atmosphere, taken with JWST NIRISS/SOSS. The 0.6–2.85 μm transmission spectrum shows evidence for muted spectral features, rejecting a perfectly flat line at >5σ. We explore water- and methane-dominated atmosphere scenarios for LTT 9779 b’s terminator, and retrieval analyses reveal a continuum of potential combinations of metallicity and cloudiness. Through comparisons to previous population synthesis works and our own interior structure modeling, we are able to constrain LTT 9779 b’s atmosphere metallicity to 20–850× solar. Within this range of metallicity, our retrieval analyses prefer solutions with clouds at millibar pressures, regardless of whether the atmosphere is water or methane dominated—though cloud-free atmospheres with metallicities >500× solar cannot be entirely ruled out. By comparing self-consistent atmosphere temperature profiles with cloud condensation curves, we find that silicate clouds can readily condense in the terminator region of LTT 9779 b. Advection of these clouds onto the dayside could explain the high dayside albedo previously inferred for this planet and be part of a feedback loop aiding the survival of LTT 9779 b’s atmosphere in the hot Neptune desert.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".