All‐Dielectric Metawaveguide Ring Resonators with Deeply Sub‐Diffractive Mode Volumes
Bibliographic record
Abstract
Abstract Whispering gallery mode (WGM) resonators provide an essential platform for various optical applications but are typically limited to mode volumes V ≈2πR(λ0/2n)2 where R is the bend radius and n is the refractive index. Here, the theory, simulation, and experimental realization of WGM resonators capable of achieving deeply sub‐diffractive mode volumes are presented, V << 2πR(λ0/2n)2, while preserving high Q factors. Rather than relying on plasmonics to reduce the mode volume, the work relies on all‐dielectric metamaterial waveguides that support localized field enhancements within the high index medium. Combined with the excitation of standing wave rather than traveling wave WGM resonances, it is shown how the mode volume of a silicon microring resonator can be reduced by factors >10 – 100 depending upon nanostructure dimensions and choice of cladding. The analysis further suggests a lower bound for the sub‐diffractive all‐dielectric mode volume, Vmin’, which scales in proportion to the mode order m times the refractive index raised to the seventh power, i.e.: Vmin’ ≈mn−7. Experimentally, these sub‐diffractive WGM devices are shown to support standing wave resonances while maintaining high intrinsic quality factors ≈104–105. These metawaveguide ring resonators present a promising WGM platform for interfacing wavelength‐scale optics with sub‐wavelength matter.
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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) | 0.000 | 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".