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Record W4403092950 · doi:10.3847/1538-4357/ad686a

The Observational and Numerical Analysis of the Rayleigh–Taylor Instability beneath a Hedgerow Prominence

2024· article· en· W4403092950 on OpenAlexfundno aff
T. Rees-Crockford, E. Scullion, E. Khomenko, Á. de Vicente

Bibliographic record

VenueThe Astrophysical Journal · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
FundersIrish Centre for High-End ComputingMinisterio de Ciencia e InnovaciónRoyal Swedish Academy of SciencesTrinity College DublinScience and Technology Facilities CouncilInstituto de Astrofísica de CanariasQueen's UniversityIrish Research CouncilEuropean Research CouncilScience Foundation IrelandQueen's University Belfast
KeywordsPhysicsRayleigh–Taylor instabilityInstabilityObservational studyRayleigh scatteringAstrophysicsAstronomyMechanicsOpticsMedicine

Abstract

fetched live from OpenAlex

Abstract Using Swedish 1 m Solar Telescope Crisp Imaging Spectro-Polarimeter 6563 Å (H α ) observations and Mancha3D simulations, we analyze the formation and evolution of falling knots beneath a hedgerow prominence. By comparing the observed knot widths and kinematics to those of a parametric survey of simulations, we estimate the range of magnetic field values and characteristic wavelengths to test if the magnetic Rayleigh–Taylor instability (MRTI) can provide a physically meaningful explanation. We recover observational parameters using a novel semiautomated method and find knot velocities with a mean of −9.68 km s −1 and a mean width of 614 km. Our simulations survey a range of critical wavelengths, λ c , of 100 to 500 km, and magnetic field strengths, B 0 , of 1 to 20 G, finding the closest match to observations around λ c = 300 km, and B 0 = 2 to 6 G. As both the observational and simulated values match expected values, we conclude that the MRTI can provide a physically meaningful explanation of this observation. Additionally, we also predict that the Daniel K. Inouye Solar Telescope will be able to observationally recover secondary instabilities on the leading edge of the falling mass through applying a point-spread function to an example from the simulated results.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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 designObservational
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

Citations5
Published2024
Admission routes1
Has abstractyes

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