Application and optimization of PML ABC for the 3-D wave equation in the time domain
Bibliographic record
Abstract
A three-dimensional algorithm with the perfectly matched layer (PML) absorbing boundary condition (ABC) for the scalar wave equation in the time domain is presented for general inhomogeneous lossy or loss-free problems. The proposed PML ABC is applicable to practical finite difference schemes treating the time-domain wave equation, such as the time-domain wave-potential (TDWP) technique and the time-domain scalar wave equation approaches to the analysis of optical structures. The time-domain wave equation for lossy media is expressed in terms of stretched coordinate variables. The algorithm is tested for homogeneous and inhomogeneous media. We demonstrate applications to open (radiation) problems and to port terminations in high-frequency circuit problems. New PML conductivity profiles are developed for use with the second order wave equation, which offer lower reflections in a wider frequency band in comparison with the commonly used (in finite-difference time-domain (FDTD) algorithms) profiles. The effect of the termination walls on the overall PML performance is studied and the best choices are singled out.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".