Asymmetric Transmission and Diffraction Engineering in Ultrathin media via Coupled Metasurfaces
Bibliographic record
Abstract
Abstract Realizing zero‐static power directional dependence of far‐field response such as asymmetric transmission (AT) in subwavelength‐thickness media at photonic wavelengths is one of the grand challenges in optoelectronics today. Structures exhibiting such behavior can unlock a range of platforms with huge societal impacts, such as directionally sensitive beam splitting, optical isolators and diodes, ultracompact cavities, and various signal multiplexing devices. Typically, asymmetric responses are achieved through breaking time‐reversal symmetry using an external magnetic field, time‐varying media, or nonlinear materials. Although these nonreciprocal systems are immune to backscattering, they suffer from the need for exotic material platforms and volatile external biases that make them susceptible to noise and drift. Here, grating‐insulator‐grating (GIG) compound metasystems hosted on a silicon nitride membrane platform providing AT in a fully passive, reciprocal noise‐free architecture are introduced. It is shown that controlling the cross‐talk between the two metasurfaces in such metasystems enables the widest AT in subwavelength‐thickness structures reported to date across telecom frequencies through engineering the density of states confined within the compound structure. The universality of the proposed design space is showcased by realizing tunable broadband response in both plasmonic and dielectric systems made from gold and silicon without the need for any external stimuli.
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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".