AN EFFICIENT MODAL FDTD FOR ABSORBING BOUNDARY CONDITIONS AND INCIDENT WAVE GENERATOR IN WAVEGUIDE STRUCTURES
Bibliographic record
Abstract
When the finite-difference time-domain method is used to compute waveguide structures, incident waves are needed for calculating electrical parameters (e.g., the scattering parameters), and effective absorbing boundary conditions are required for terminating open waveguide structures.The incident waves are conventionally obtained with inefficient three-dimensional (3D) simulations of long uniform structures, while the absorbing boundary conditions reported so far do not perform well at or below cut-off frequencies.To address the problems, we propose a novel one-dimensional (1D) finitedifference time-domain method in this paper.Unlike the other methods developed so far, the proposed method is derived from the finite-difference time-domain formulation, and therefore has the same numerical characteristics as that of the finite-difference time-domain method.As a result, when used to obtain an incident wave, it produces results almost identical to those produced by the conventional finitedifference time-domain method except computer rounding-off errors.When used as the absorbing boundary condition, it produces reflections of less than -200 dB in entire frequency spectrum including the cut-off frequencies.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".