Fiber-chip edge coupler with large mode size for silicon photonic wire waveguides
Bibliographic record
Abstract
Fiber-chip edge couplers are extensively used in integrated optics as one of the key structures for coupling of light between planar waveguide circuits and optical fibers. In this work, a new fiber-chip edge coupler concept with large mode size for coupling to submicrometer silicon photonic wire waveguides is presented. The coupler allows direct coupling to conventional SMF-28 optical fiber and circumvents the need for lensed fibers. We demonstrate by simulations a 95% mode overlap between the mode at the chip facet and a high numerical aperture single mode optical fiber with 6 μm mode field diameter (MFD). We also demonstrate a modified design with 89% overlap between the mode at the chip facet and a standard SMF-28 fiber with 10.4 μm MFD. The coupler is designed for 220 nm silicon-oninsulator (SOI) platform. An important advantage of our coupler is that large mode size is obtained without the need to increase buried oxide (BOX) thickness, which in our design is set to 3 μm. This remarkable feature is achieved by implementing in the SiO2 upper cladding two thin high-index Si3N4 layers. The high-index layers increase the effective refractive index of the upper cladding layer near the facet and are gradually tapered out along the coupler to provide adiabatic mode transformation to the silicon wire waveguide. Simultaneously, the Si-wire waveguide is inversely tapered along the coupler. The mode overlap at the chip facet is studied using a vectorial 2D mode solver and the mode transformation along the coupler is studied by 3D Finite-Difference Time-Domain simulations. The couplers are optimized for operating with transverse electric (TE) polarization and the operating wavelength is centered at 1.55 μm.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".