Numerical Error Analysis and Control in a Dynamically Adaptive Mesh Refinement (AMR) - FDTD Technique
Why this work is in the frame
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Bibliographic record
Abstract
A recently proposed dynamically adaptive mesh refinement (AMR) finite-difference time-domain (FDTD) technique has been shown to achieve several tens of execution time savings compared to the conventional FDTD, when applied to practical microwave design and analysis problems. Yet, its performance depends on several a priori defined parameters, in a way similar to frequency domain mesh adaptive techniques. The estimation of this dependence, as well as the derivation of related error bounds, is contributed by this paper, being achieved via numerical studies and confirmed through specific applications. With such estimates in place, applying this technique and obtaining its theoretically demonstrated advantages is greatly facilitated for the end user in the microwave community
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it