Flares on TRAPPIST-1 Reveal the Spectrum of Magnetic Features on Its Surface
Bibliographic record
Abstract
Abstract TRAPPIST-1 is an M8 dwarf hosting seven known exoplanets and is currently one of the most frequently observed targets of the James Webb Space Telescope (JWST). However, it is notoriously active, and its surface is believed to be covered by magnetic features that contaminate the planetary transmission spectra. The radiative spectra of these magnetic features are needed to clean transmission spectra, but they currently remain unknown. Here, we develop a new approach for measuring these spectra using time-resolved JWST/NIRISS observations. We detect a persistent postflare enhancement in the spectral flux of TRAPPIST-1. Our analysis rules out lingering flare decay as the cause of the flux enhancement and thus, points to structural changes on the stellar surface induced by flares. We suggest that the flaring event triggers the disappearance of (part of) a dark magnetic feature, producing a net brightening. This suggestion is motivated by solar data: flare-induced disappearance of magnetic features on the solar surface has been directly detected in high spatial resolution images, and our analysis shows that this process produces changes in solar brightness very similar to those we observe on TRAPPIST-1. The proposed explanation for the flux enhancement enables, to our knowledge, the first measurement of the spectrum of a magnetic feature on an M8 dwarf. Our analysis indicates that the disappearing magnetic feature is cooler than the TRAPPIST-1 photosphere, but by at most a few hundred kelvins.
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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".