Scalable Two-Mode 3-Port and 4-Port Mode Insensitive Silicon Photonic Switches
Bibliographic record
Abstract
We propose and experimentally demonstrate a novel design approach for scalable 3-port and 4-port mode insensitive multimode switching matrices for the first two quasi-transverse electric (TE) modes. The mode insensitive phase shifter ensures less power consumption for simultaneous multimode signal transmission in a mode division multiplexing (MDM) network. At 1550 nm, the 3-port switch exhibits approximately 2.6 dB and 3.3 dB insertion loss for the longest path with a crosstalk of at most 10 dB and 8 dB over a bandwidth of 40 nm (1530 nm to 1570 nm) for${\mathrm {TE}}_{\mathrm {0}}$and${\mathrm {TE}}_{\mathrm {1}}$modes, respectively. The insertion loss measured for the 4-port switch is approximately 2.7 dB and 3.6 dB at 1550 nm with a corresponding crosstalk less than 8 dB for the two TE modes, respectively. The payload transmission is also performed using both 10 Gb/s non-return-to-zero (NRZ) and 14.0625 Gbaud 4-level pulse-amplitude modulation (PAM4) pseudorandom binary sequence (PRBS)-31 data signal to analyze the performance of the switches. Clear open eyes are observed for both single-mode and simultaneous two-mode transmissions. The low insertion loss, low intermodal crosstalk over a large optical bandwidth, and the clear open eye validate the scalability of the proposed switches for larger port count and higher-order modes.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".