Escaping Helium and a Highly Muted Spectrum Suggest a Metal-enriched Atmosphere on Sub-Neptune GJ 3090 b from JWST Transit Spectroscopy
Bibliographic record
Abstract
Abstract Sub-Neptunes, the most common planet type, remain poorly understood. Their atmospheres are expected to be diverse, but their compositions are challenging to determine, even with JWST. Here, we present the first JWST spectroscopic study of the warm sub-Neptune GJ 3090 b (2.13 R ⊕, T eq,A = 0.3 ∼ 700 K), which orbits an M2V star, making it a favorable target for atmosphere characterization. We observed four transits of GJ 3090 b: two each using JWST NIRISS/SOSS and NIRSpec/G395H, yielding wavelength coverage from 0.6 to 5.2 μm. We detect the signature of the 10833 Å metastable helium triplet at a statistical significance of 5.5σ with an amplitude of 434 ± 79 ppm, marking the first such detection in a sub-Neptune with JWST. This amplitude is significantly smaller than predicted by solar-metallicity forward models, suggesting a metal-enriched atmosphere that decreases the mass-loss rate and attenuates the helium feature amplitude. Moreover, we find that stellar contamination, in the form of the transit light source effect, dominates the NIRISS transmission spectra, with unocculted spot and faculae properties varying across the two visits separated in time by approximately 6 months. Free retrieval analyses on the NIRSpec/G395H spectrum find tentative evidence for highly muted features and a lack of CH4. These findings are best explained by a high-metallicity atmosphere (>100× solar at 3σ confidence for clouds at ∼μbar pressures) using chemically consistent retrievals and self-consistent model grids. Further observations of GJ 3090 b are needed for tighter constraints on the atmospheric abundances and to gain a deeper understanding of the processes that led to its potential metal enrichment.
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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 | 0.000 |
| 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".