Characterization and excitation of a nano-scaled plasmonic coupler with co-directional phase and contra-directional power flow
Bibliographic record
Abstract
A nano-scaled coupled-waveguide coupler based on the guidance of surface plasmon-polaritons (SPPs) is proposed, designed and simulated at optical frequencies. The basic structure of the coupler comprises layered dielectric materials and thin silver films, which serve as two stacked nano-transmission lines to achieve broadside coupling. The key property of this design is that it operates based on the principle of contra-directional coupling between a left-handed and a right-handed guided wave, giving rise to supermodes that are characterized by complex-conjugate propagation constants (even in the absence of losses), where the attenuation constant signifies the rate of coupling instead of the conventional power dissipation. The resulting exponential attenuation along the coupler leads to dramatically reduced coupling lengths compared to previously reported co-directional SPP couplers (e.g. from millimeters to sub-microns). Given its size, the device lends itself to form the building block of a functional matrix such as a switching array in nanophotonics applications, for example. In order to verify the contra-directional coupling theory and to characterize our design, we also propose and examine several possible excitation schemes, such as using a plasmonic dipole antenna and a grating structure to excite the SPP mode. Additionally, a measurement topology utilizing a curved plasmonic waveguide is also presented in this paper.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".