Tunable optical delay line in SOI implemented with step chirped Bragg gratings and serial grating arrays
Bibliographic record
Abstract
Tunable optical delay devices have numerous applications in optical communications [1] and have been successfully implemented using slow light elements and fiber or waveguide gratings. There has been considerable interest in siliconon- insulator (SOI) as a technology platform for compact integration of optical signal processing systems. SOI-based delay lines have been realized using coupled ring resonators [2], photonic crystals [3], and various Bragg grating-based configurations including single or coupled chirped sidewall gratings [4,5] as well as tapered rib waveguide gratings [6]. By linearly chirping the period in sidewall gratings, relatively small delays (a few ps) over a bandwidth of tens of nm were demonstrated [4]; with tapered waveguides, significantly larger delays (300-500 ps) were obtained, albeit over a narrower bandwidth (< 2 nm) [6]. On the other hand, some signal processing applications may require large delays (e.g., tens to hundreds of ps) over large bandwidths (several to tens of nm). Several designs have been proposed to meet these requirements, e.g., a step-chirped rib waveguide grating providing 50 ps delay over 15 nm [7] or complementary apodized sidewall gratings providing up to 275 ps over 3 nm [8], however, they have not been realized experimentally. In this paper, we demonstrate discretely tunable optical delay lines that provide tens of ps delay (up to 65 ps) in steps of 15-32 ps over bandwidths of several tens of nm (35-70 nm). The devices are fabricated on SOI using electron beam lithography and implemented through two different approaches: serial sidewall Bragg grating arrays and the step-chirped sidewall Bragg gratings.
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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 | 0.001 |
| 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 | 0.000 |
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".