A Hubble PanCET Study of HAT-P-11b: A Cloudy Neptune with a Low Atmospheric Metallicity
Bibliographic record
Abstract
Abstract We present the first comprehensive look at the 0.35–5 μm transmission spectrum of the warm (∼800 K) Neptune HAT-P-11b derived from 13 individual transits observed using the Hubble and Spitzer Space Telescopes. Along with the previously published molecular absorption feature in the 1.1–1.7 μm bandpass, we detect a distinct absorption feature at 1.15 μm and a weak feature at 0.95 μm, indicating the presence of water and/or methane with a combined significance of 4.4σ. We find that this planet’s nearly flat optical transmission spectrum and attenuated near-infrared molecular absorption features are best matched by models incorporating a high-altitude cloud layer. Atmospheric retrievals using the combined 0.35–1.7 μm Hubble Space Telescope (HST) transmission spectrum yield strong constraints on atmospheric cloud-top pressure and metallicity, but we are unable to match the relatively shallow Spitzer transit depths without underpredicting the strength of the near-infrared molecular absorption bands. HAT-P-11b’s HST transmission spectrum is well matched by predictions from our microphysical cloud models. Both forward models and retrievals indicate that HAT-P-11b most likely has a relatively low atmospheric metallicity (<4.6 Z ⊙ and <86 Z ⊙ at the 2σ and 3σ levels respectively), in contrast to the expected trend based on the solar system planets. Our work also demonstrates that the wide wavelength coverage provided by the addition of the HST STIS data is critical for making these inferences.
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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 | 0.001 | 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) | 0.001 | 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".