The impact of loss on plasmonic resonances in a slit in a real metal
Bibliographic record
Abstract
There is a common misconception that a narrower slit leads to more enhancement but in the presence of loss, the narrowest slit does not give the highest field enhancement which is important for SERS and nonlinear optics applications. Here, the impact of loss on the plasmonic resonances in metal-insulator-metal slits is analyzed. The reflection of TM light in a subwavelength slit in a real metal has been calculated using mode matching theory and orthogonality principle of electric and magnetic field for a real metal exhibiting both dispersion and loss. Then the calculated reflection phase has been used to calculate plasmonic resonances. The impact of metal loss and the presented theory on plasmonic resonances is investigated. The theoretical calculations agree well with comprehensive simulations, but differ substantially from the conjugated orthogonality result, as was used in past analytical works, showing promise for simple theoretical investigation of future plasmonic MDM structures.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".