Efficient sensitivity analysis of surface plasmon waveguide structures
Bibliographic record
Abstract
We propose a novel approach for efficient sensitivity analysis and design optimization of surface plasmon polaritons (SPPs) based waveguide structures. This approach has been utilized to analyze and propose novel designs of different structures. It has been exploited to design a novel SPP waveguide using a metal loaded on silicon on insulator (SOI) for subwavelength applications. In this design, the SOI material is utilized due to its wide application in electronic circuits. It also allows for strong guiding and hence subwavelength light confinement. The utilized metal is gold (Au) at a wavelength of 1.55 μm. The effect of the different design parameters of this structure on the propagation length of the fundamental TM mode is efficiently studied using the proposed approach. The imaginary distance 3D ADI BPM is utilized to calculate the propagation length. The sensitivity information is then estimated using the adjoint variable method without any additional simulations. The same approach is utilized to propose an optimized design of new 1x3 SPP power splitter/combiner using metal on insulator. In this design the multimode interference phenomenon is utilized. Our goal is to minimize the insertion loss for practical applications. The optimized design has a low insertion loss of 1.5 dB and compact size.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".