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Record W4416388404 · doi:10.3847/2041-8213/ae1960

Separating Flare and Secondary Atmospheric Signals with <tt>RADYN</tt> Modeling of Near-infrared JWST Transmission Spectroscopy Observations of TRAPPIST-1

2025· article· en· W4416388404 on OpenAlexaff
Ward S. Howard, Adam F. Kowalski, Michael Radica, Laura Flagg, Valeriy Vasilyev, Benjamin V. Rackham, Guadalupe Tovar Mendoza, Meredith A. MacGregor, A. I. Shapiro, Jake Taylor, Louis-Philippe Coulombe, Olivia Lim, David Lafreniére

Bibliographic record

VenueThe Astrophysical Journal Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsUniversité de Montréal
FundersSpace Telescope Science Institute
KeywordsFlareSolar flareSpectral lineSpectroscopyRadiationBinExtreme ultravioletPlanet

Abstract

fetched live from OpenAlex

Abstract Although TRAPPIST-1’s temperate planets have the highest transmission signals of any known system, flares contaminate 50%–70% of transits at the 1000 ppm level, far above 100 ppm secondary atmospheric signals. Efforts to mitigate flare contamination and assess impacts on radiation environments are each hampered by a lack of empirical spectral analysis and physics-based modeling. We present spectrotemporal analysis and radiative-hydrodynamic modeling of 5.5 hr of NIRISS and NIRSpec observations of six TRAPPIST-1 flares of 2.2–8.7 × 10 30 erg. The flare lines and continua are characterized using grid searches of RADYN beam-heating models spanning 10 4 times in electron beam parameters. Best-fit models indicate these flares result from moderate-intensity beams with emergent electron fluxes of F e = 10 12 erg s −1 cm −2 and energies ≤37 keV, although all models overpredict the Paschen jump. These models predict X-ray and extreme UV (XUV), far-UV, and near-UV counterparts to the IR peak fluxes of 8.9–28.9 × 10 27 , 4.3–13.9 × 10 26 , and 3.4–11.4 × 10 27 erg s −1 , respectively. Scaling the flare rate into the XUV suggests flaring contributes 1.35 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msubsup> <mml:mrow/> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>0.15</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>2.0</mml:mn> </mml:mrow> </mml:msubsup> <mml:mspace width="0.25em"/> <mml:mo>×</mml:mo> </mml:math> quiescence yr −1 . We bin integrations of similar flare effective temperature to construct fiducial flare spectra from 2000 to 4500 K, in order to develop separate empirical and RADYN -based mitigation pipelines. Both pipelines are applied to all 5.5 hr of R = 10 data, resulting in maximum residuals from 1 to 2.8 μ m of 100–140 ppm and typical residuals of 54 ± 14 and 65 ± 17 ppm for the empirical and RADYN -based pipelines, respectively. Injection testing supports a 3 σ detection capability for CO 2 atmospheres with features of 150–250 ppm, with weak evidence (Bayes factor ≈ 3) still obtained at 130 ppm. Our results motivate multiwavelength observations to improve model fidelity and test high-energy predictions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.221
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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