用于神经形态光学计算的自校准微oring 权重函数

J. Garcia-Echeverria, D. Musat, A. Mahsafar, K. R. Mojaver, D. Rolston, G. Cowan, O. Liboiron-Ladouceur
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引用次数: 0

摘要

本文介绍了一种基于微oring 谐振器的权重函数,该函数适用于非形态光子应用,对于 2 Gbps 输入光信号,其精度达到了创纪录的 11.3 位,准确度达到了 9.3 位。该系统采用全模拟自参照比例积分派生(PID)控制器,在高达 60 摄氏度的范围内实现实时温度稳定。在 6 摄氏度范围内演示了自校准权重功能,只需进行一次初始校准,且精度和准确度下降极小。通过使用可变增益跨阻抗放大器监测微孔的直通端口和下降端口,实现了精确的砝码调整,确保了最佳性能和可靠性。这些发现强调了该系统对动态热环境的鲁棒性,凸显了高速可重构模拟光子网络的潜力。
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Self-calibrated Microring Weight Function for Neuromorphic Optical Computing
This paper presents a microring resonator-based weight function for neuromorphic photonic applications achieving a record-high precision of 11.3 bits and accuracy of 9.3 bits for 2 Gbps input optical signals. The system employs an all-analog self-referenced proportional-integral-derivative (PID) controller to perform real-time temperature stabilization within a range of up to 60 degree Celsius. A self-calibrated weight function is demonstrated for a range of 6 degree Celsius with a single initial calibration and minimal accuracy and precision degradation. By monitoring the through and drop ports of the microring with variable gain transimpedance amplifiers, accurate and precise weight adjustment is achieved, ensuring optimal performance and reliability. These findings underscore the system's robustness to dynamic thermal environments, highlighting the potential for high-speed reconfigurable analog photonic networks.
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