Compact grating coupler between vertically stacked silicon-on-insulator waveguides
Bibliographic record
Abstract
The area of integrated optical circuits has been undergoing rapid development due to the important applications of fiber communication systems and optical interconnects. A significant challenge of photonic circuits is to increase circuit density and to miniaturize these devices. The vertical integration of stacked waveguides for photonic circuits onto a single substrate is a promising configuration to enable the dense monolithic integration of three-dimensional photonic devices. Application of high-index-contrast waveguides, such as silicon-on-insulator waveguides, is another important way to increase the density of optical circuits due to their small sizes. These waveguides produce high confinement in the guiding layers and have the advantages of compactness and immunity of cross-talk between different waveguides. It is thus expected that efficient coupling of light between vertically integrated waveguides where no direct field-overlap of guided modes exists is a key issue. We propose a compact double-grating coupler to realize efficient coupling through radiation modes between two vertically stacked SOI waveguides. The grating is strong enough to be considered as a onedimensional photonic bandgap structure which facilitates a very short coupling length. Simulations suggest that a 22% efficiency is achievable in coupling light from one waveguide to another with a 12.9μm long grating. We find that the coupling efficiency is enhanced by Fabry-Perot resonance between two gratings. Coupling efficiency can be dramatically increased by incorporating a reflective under-layer structure or using blazed grating.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".