Efficient calculations of dispersive properties of photonic crystals using the transmission line matrix method
Bibliographic record
Abstract
In this paper, we present an analysis of the accuracy and efficiency of different approaches for the simulation of photonic crystals using the transmission line matrix method. The approaches that we present can be divided into two categories: complex- and real-valued algorithms using a uniform mesh, and complex- and real-valued algorithms using a multigrid mesh. The advantages and disadvantages of each approach are discussed and a brief comparison between these methods is made from the points of view of computational expense and accuracy. It is found that a combination of a real-valued method in a multigrid mesh results in the most efficient algorithm. However, while the complex-valued formulation is valid for the analysis of any photonic crystal, the applicability of the real-valued formulation is limited by structural constraints requiring cell symmetries. It is also found that a multigrid approach can considerably reduce the computational cost required for simulating photonic crystals and our results indicate that a good compromise between accuracy and computational cost can be found. Various photonic crystals are simulated by applying these approaches, and the results are validated using alternative methods.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".