High-performance silicon photonic tri-state switch based on balanced nested Mach-Zehnder interferometer
Bibliographic record
Abstract
ABSATRCT: This work proposes a novel silicon photonic tri-state (cross/bar/blocking) switch, featuring high-speed switching, broadband operation, and crosstalk-free performance. The switch is designed based on a 2 × 2 balanced nested Mach-Zehnder interferometer structure with carrier injection phase tuning. As compared to silicon photonic dual-state (cross/bar) switches based on Mach-Zehnder interferometers with carrier injection phase tuning, the proposed switch not only has better performance in cross/bar switching but also provides an extra blocking state. The unique blocking state has a great advantage in applications of N × N switch fabrics, where idle switching elements in the fabrics can be configured to the blocking state for crosstalk suppression. According to our numerical experiments on a fully loaded 8 × 8 dilated Banyan switch fabric, the worst output crosstalk of the 8 × 8 switch can be dramatically suppressed by more than 50 dB, by assigning the blocking state to idle switching elements in the fabric. The results of this work can extend the functionality of silicon photonic switches and significantly improve the performance of on-chip N × N photonic switching technologies.
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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 | 0.001 |
| 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".