Ultra-low loss optical delay lines based on silicon nitride SWG technology
Bibliographic record
Abstract
Optical delay lines are essential for microwave photonics and optical signal processing applications. This work presents the design, optimization, and experimental demonstration of compact optical delay lines using subwavelength grating (SWG) structures on a silicon nitride platform. By leveraging the low-loss properties of silicon nitride, our approach reduces the insertion loss compared to silicon-based alternatives. We propose optimized SWG tapers with a loss of 0.04 dB per taper for a 15 µm taper length and SWG bends achieving 0.82 dB loss per 90° bend using 20 µm radius. Our results show a linear relationship between group delay and the SWG duty cycle, offering a tunable delay mechanism without increasing the waveguide length. The fabricated delay lines demonstrate a 1.6 dB/cm loss and significantly improved performance over previously reported silicon-based SWG delay lines. These findings highlight the potential of silicon nitride SWG structures for high-performance, compact optical delay lines in photonic integrated circuits.
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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) | 0.000 | 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".