Affiliation:
1. National University of Defense Technology
2. The Hong Kong Polytechnic University
3. Hu’nan Key Laboratory of Mechanism and Technology of Quantum Information
Abstract
Multi-mode multiplexing optical interconnection (MMOI) has been widely used as a new technology that can significantly expand communication bandwidth. However, the constant-on state of each channel in the existing MMOI systems leads to serious interference for receivers when extracting and processing information, necessitating introducing real-time selective-on function for each channel in MMOI systems. To achieve this goal, combining several practical requirements, we propose a real-time selective mode switch based on phase-change materials, which can individually tune the passing/blocking of different modes in the bus waveguide. We utilize our proposed particle swarm optimization algorithm with embedded neural network surrogate models (NN-in-PSO) to design this mode switch. The proposed NN-in-PSO significantly reduces the optimization cost, enabling multi-dimensional simultaneous optimization. The resulting mode switch offers several advantages, including ultra-compactness, rapid tuning, nonvolatility, and large extinction ratio. Then, we demonstrate the real-time channel selection function by integrating the mode switch into the MMOI system. Finally, we prove the fabricating robustness of the proposed mode switch, which paves the way for its large-scale application.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Foundation of NUDT
Natural Science Foundation of Hunan Province
Program for New Century Excellent Talents in University
Postgraduate Scientific Research Innovation Project of Hunan Province, China