Broadband high-efficiency zero-order surface grating coupler for the near- and mid-infrared wavelength ranges
Bibliographic record
Abstract
Efficient coupling of light from a chip into an optical fiber is a major issue in silicon photonics, as the dimensions of high-index-contrast photonic integrated waveguides are much smaller than conventional fiber diameters. Surface grating couplers address the coupling problem by radiating the optical power from a waveguide through the surface of the chip to the optical fiber, or vice versa. However, since the grating radiation angle substantially varies with the wavelength, conventional surface grating couplers cannot offer high coupling efficiency and broad bandwidth simultaneously. To overcome this limitation, for the near-infrared band we have recently proposed SOI-based zero-order grating couplers, which, making use of a subwavelength-engineered waveguide and a high-index prism, suppress the explicit dependence between the radiation angle and the wavelength, achieving a 1-dB bandwidth of 126 nm at λ = 1.55 μm. However, in the near-infrared, the bandwidth enhancement of zero-order grating couplers is limited by the effective index wavelength dispersion of the grating. In the mid-infrared spectral region, the waveguide dispersion is lower, alleviating the bandwidth limitation. Here we demonstrate numerically our zero-order grating coupler concept in the mid-infrared at λ = 3.8 μm. Several couplers for the silicon-on-insulator and the germanium-on-silicon nitride platforms are designed and compared, with subdecibel coupling efficiencies and 1-dB bandwidths up to ~680 nm.
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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".