A Numerical Technique for Computing the Values of Plane Wave Scattering Coefficients of a General Scatterer
Bibliographic record
Abstract
The results of a numerical technique for computing the plane wave scattering coefficients of a general scatterer are presented. The technique is tailored herein to the case where the scatterer is a general slab and the technique is implemented with the FDTD method of the scattered field formulation. Since the technique relies on the use of a Maxwellian beam of dominant polarization as the excitation within the FDTD simulation, this paper presents also an improved scheme for synthesizing such a beam. Window averaging is also presented as a new scheme for mitigating the effects of aperture truncation. Validation of the technique revealed that the use of a non-Maxwellian Gaussian beam of uniform polarization produced erroneous values of the plane wave scattering coefficients. When used with a Maxwellian beam excitation, however, the technique showed to be trustworthy, stable and accurate, even for lossy media. Convergence test results revealed that the accuracy of the values of plane wave scattering coefficients decreased much faster as the conductivity of the medium increased than what would be expected from numerical anisotropy. Finally, poor accuracy results are reported when the scattered field illuminates strongly the edges or corners of the integration box around a finite-size slab.
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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 | 0.001 |
| 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".