Metallic superlens designed with close-to-cutoff of long-range SPP mode
Bibliographic record
Abstract
The metallic superlens of a single negative permittivity is easier to implement than the double negative material superlens and can be applied to nano-scale resolution lithography. The metallic superlens amplifies by the resonance the surface plasmon polariton (SPP) waves, which carry the sub-wavelength detail information of the object. However, the excitations of the long- and the short-range SPP modes of the metal slab lead to two peaks in the transfer function which enhance the spatial frequencies disproportionally, resulting in strong sidelobes in the image. Conventionally the metallic superlens is designed by trials without rules to follow. We propose to design the metallic superlens by approaching the cutoff condition of the long-range SPP mode in order to flatten the transfer function and to improve the imaging performance significantly. Design experiments of Al and Ag superlens with both the transfer-matrix approach and the numerical Finite Difference in Time Domain method are shown.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".