Weather on Other Worlds. IV. Hα Emission and Photometric Variability Are Not Correlated in L0–T8 Dwarfs
Bibliographic record
Abstract
Abstract Recent photometric studies have revealed that surface spots that produce flux variations are present on virtually all L and T dwarfs. Their likely magnetic or dusty nature has been a much-debated problem, the resolution to which has been hindered by paucity of diagnostic multi-wavelength observations. To test for a correlation between magnetic activity and photometric variability, we searched for Hα emission among eight L3–T2 ultra-cool dwarfs with extensive previous photometric monitoring, some of which are known to be variable at 3.6 μm or 4.5 μm. We detected Hα only in the non-variable T2 dwarf 2MASS J12545393−0122474. The remaining seven objects do not show Hα emission, even though six of them are known to vary photometrically. Combining our results with those for 86 other L and T dwarfs from the literature show that the detection rate of Hα emission is very high (94%) for spectral types between L0 and L3.5 and much smaller (20%) for spectral types ≥L4, while the detection rate of photometric variability is approximately constant (30%–55%) from L0 to T8 dwarfs. We conclude that chromospheric activity, as evidenced by Hα emission, and large-amplitude photometric variability are not correlated. Consequently, dust clouds are the dominant driver of the observed variability of ultra-cool dwarfs at spectral types, at least as early as L0.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".