A hybrid FDTD and leapfrog ADI-FDTD method with PML implementation
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Bibliographic record
Abstract
In this paper, a hybrid FDTD and leapfrog alternating-direction-implicit finite-difference time-domain (ADI-FDTD) method is presented. The perfectly matched layer (PML) absorbing boundary conditions are also incorporated in the method and non-uniform grids are deployed to efficiently model electromagnetic radiation and scattering in open domains. In the proposed hybridization method, the leapfrog ADI-FDTD is applied to regions of fine grids, while the FDTD is applied to regions of coarse grids. As a result, a single relatively large time step can be used uniformly over a complete solution domain; this yields a significant CPU time reduction in comparison with the conventional FDTD while maintaining accuracy with fine grid regions. The effectiveness and efficiency of the proposed hybrid method are validated and evaluated with numerical results.
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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) | 0.001 | 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 it