SOI-based 2-D mems L-switching matrix for optical networking
Bibliographic record
Abstract
Two-dimensional microelectromechanical system (2-D MEMS) optical switches have been widely demonstrated in research laboratories and in the industry. A novel switching architecture, the L-switching matrix, that decreases the most distance free space path length and the difference between the most and least distance paths while maintaining nonblocking port switching capacity has been proposed and demonstrated. Collimators with optimized beam waist are selected such that the insertion loss of the average beam path is the lowest. Larger beam waists are used to accommodate for the diffraction effects of the Gaussian beam of the most distance path. However, larger beam waists require larger mirror areas to avoid beam-clipping and losses due to angular misalignment are more acute. Therefore, having shorter absolute and relative path lengths will avoid the beam-clipping effects and increase the port-to-port loss uniformity of the optical switch. The unique architecture of the L-switching matrix which utilizes a double-sided mirror can theoretically increase the maximum port-count to 64×64 or decrease the current insertion loss of a 32×32 MEMS switch by 50%. Moreover, the L-switching matrix requires 25% less mirrors and electrodes than a conventional cross bar architecture. A fabrication process involving silicon-on-insulator (SOI) wafers has been defined to fabricate the double-sided mirrors used in the L-switching matrix.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".