Broadband slow light in genetically optimized coupled-cavity waveguides with GBP exceeding 0.45
Bibliographic record
Abstract
Slow light propagation through engineered band dispersion in photonic structures is a highly promising tool for realizing integrated optical delay lines and efficient photonic devices through enhanced optical nonlinearities [1, 2]. A primary goal is to achieve devices with large, approximately constant group index over the largest possible bandwidth, thus enabling multimode and pulsed operation [2]. We present an experimental proof of record high group-index bandwidth product (GBP = ng Αω/ω) [2] in genetically optimized coupled-cavity waveguides (CCWs) made of staggered L3 photonic crystal cavities (Fig.1(a) and (b)). The optimization procedure [3] was applied to the unit cell (Fig. 1(a)) to achieve maximal GBP combined with low losses. The resulting designs [4] were realized in Si slabs (Fig. 1(b)), where CCWs of length ranging between 50 and 800 cavities were fabricated. The samples were characterized by measuring the CCW transmission (Fig. 1(c) and (d)), the mode dispersion through Fourier-space imaging, and the group index ng with Mach-Zehnder interferometry (Fig. 1(e)). Various cavity designs were investigated, with theoretical group index ranging from ng=37 to ng>100. Record-high GBP=0.45 was demonstrated over a bandwidth approaching 20nm (Fig. 1(e)), with ng=37, a very homogeneous flat-top transmission profile (Fig. 1(c) and (d), variations lower than 10 dB) and losses below 67 dB/ns. On a different design [3], an average ng=107 with 15% variation over 7.4nm was measured. These values range among the best ever demonstrated for a silicon device.
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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) | 0.001 | 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 | 0.000 | 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".