Ultra-short and highly efficient metamaterial Fresnel lens-assisted taper
Bibliographic record
Abstract
This paper demonstrates the benefits of leveraging free-space optics concepts in the design of certain integrated photonic components, leading to a footprint reduction without compromising on performance. Specifically, we present ultra-short, highly efficient and fabrication-friendly mode-size converters based on metamaterial Fresnel lens-assisted tapers. This is achieved using a parameterized inverse-design approach, where the metamaterial phase shifters are realized using fabrication-friendly Manhattan geometries, by optimizing the width, length, and position of the phase shifters. This approach overcomes the limitations of the conventional method that uses local periodic approximation, which is not suitable for lenses with a short focal length and high numerical aperture. We also extend the free-space concept of compound lenses and demonstrate a doublet-based taper to further reduce the footprint. The devices are fabricated and experimentally characterized in terms of insertion loss and signal integrity at high data transmission rates, exhibiting high performance. For the singlet, it effectively achieves mode-size conversion from 15 μ m to 0.5 μ m within a 15 μ m distance, leading to ×10 length reduction compared to a linear taper. The insertion loss is under 1 dB over the entire C-band. The doublet achieves the same mode-size reduction within a 10 μ m distance, leading to ×15 length reduction compared to a linear taper. The insertion loss is near 1 dB over most of the C-band. In both cases, the signal integrity is maintained for up to 50 Gbit/s.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 teacher head, 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".