Low-dispersive super high-order FDTD schemes
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Bibliographic record
Abstract
Recently, many efforts have been placed in developing FDTD schemes with extremely low numerical dispersion for electromagnetic modelling. Among the schemes developed so far are the pseudo-spectral time-domain (PSTD) and multi-resolution time-domain (MRTD) methods. In these, transforms are required and field quantities are computed indirectly. In this paper, we show that a systematic way of developing arbitrary high-order FDTD schemes can also achieve numerical dispersion as low as that of PSTD and MRTD. The advantages of the present method are: (1) it is simple and straightforward, as the field quantities are calculated directly; and (2) it can also achieve low spatial sampling rates down to two grid points per wavelength and yet the memory requirements are similar to those for MRTD and PSTD. Numerical examples are given to validate the method.
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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 | 0.000 |
| 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) | 0.017 | 0.001 |
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