The Observational and Numerical Analysis of the Rayleigh–Taylor Instability beneath a Hedgerow Prominence
Bibliographic record
Abstract
Abstract Using Swedish 1 m Solar Telescope Crisp Imaging Spectro-Polarimeter 6563 Å (Hα) 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.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".