Nested nonconcentric microring resonators with high-Q and large fabrication tolerance
Bibliographic record
Abstract
Microring resonators are one of the most sought-after optical components for realizing several on-chip functionalities that include sensing, data routing, new frequency generation, and quantum photonic applications. Many of these applications demand a high quality factor and large notch depth (high extinction ratio), which can be achieved by critical coupling. However, the critical coupling is very sensitive to fabrication accuracies and thermal drift. Geometrical parameters of the resonators are generally swept to attain critical coupling, where a few designs can pass the critical coupling condition criteria. In this work, we propose a methodology to circumvent this vital issue. The proposed technique is based on coupled-resonator systems where two different microrings are embedded into a larger microring, referred to as a nonconcentric nested microring resonator (NN-MRR). The NN-MRR configuration relaxes the requirement of the critical coupling condition by 20% when the strip optical waveguide has either smooth or rough sidewalls. Numerical simulations reveal that, unlike standard MRR, a high Q -factor ( > 1 0 5 ) and a large transmission notch depth > 10 d B can be maintained irrespective of the rings’ coupling conditions for the nested MRRs. Besides the extra degree of freedom of design provided by the inner rings, the other significant advantage of the proposed NN-MRR is its compactness. We believe that the nested MRR arrangement could be highly efficient for biosensing, nonlinear, and quantum applications within a broad ambient temperature range. We have fabricated the NN-MRRs in a silicon-on-insulator platform through electron beam lithography and experimentally demonstrated the theoretical and numerical findings.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".