Cloud Atlas: Variability in and out of the Water Band in the Planetary-mass HD 203030B Points to Cloud Sedimentation in Low-gravity L Dwarfs
Bibliographic record
Abstract
Abstract We use the Wide Field Camera 3 on the Hubble Space Telescope to spectrophotometrically monitor the young L7.5 companion HD 203030B. Our time series reveal photometric variability at 1.27 and 1.39 μ m on timescales compatible with rotation. We find a rotation period of hr: comparable to those observed in other brown dwarfs and planetary-mass companions younger than 300 Myr. We measure variability amplitudes of 1.1% ± 0.3% (1.27 μ m) and 1.7% ± 0.4% (1.39 μ m), and a phase lag of 56° ± 28° between the two light curves. We attribute the difference in photometric amplitudes and phases to a patchy cloud layer that is sinking below the level where water vapor becomes opaque. HD 203030B and the few other known variable young late-L dwarfs are unlike warmer (earlier-type and/or older) L dwarfs, for which variability is much less wavelength-dependent across the 1.1–1.7 μ m region. We further suggest that a sinking of the top-most cloud deck below the level where water or carbon monoxide gas become opaque may also explain the often enhanced variability amplitudes of even earlier-type low-gravity L dwarfs. Because these condensate and gas opacity levels are already well-differentiated in T dwarfs, we do not expect the same variability amplitude enhancement in young versus old T dwarfs.
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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 | 0.000 | 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".