You Mengyu, Arai Kohei, Sunada Satoshi
Opt Express. 2025 Jun 16;33(12):24982-24994. doi: 10.1364/OE.559262.
Photonic systems excel at performing linear computations, such as matrix-vector multiplications, in a highly parallel and energy-efficient manner. However, implementing nonlinear computations in photonic systems remains challenging without relying on optoelectronic conversions or nonlinear/active materials, both of which are energy-intensive. Here, we present a nonlinear computing approach for time series processing. This approach enables energy-efficient and nonlinear computations of large-scale optical networks within a single linear (passive) microcavity by leveraging the interplay between cavity modes and an optical phase-encoded input signal and facilitates an on-chip implementation on a silicon photonic platform. We experimentally demonstrate higher-order nonlinear computational capacity using a silicon photonic microcavity, achieving superior performance in time-dependent processing tasks, such as chaotic time-series prediction and nonlinear observer tasks.
光子系统擅长以高度并行且节能的方式执行线性计算，比如矩阵向量乘法。然而，在不依赖光电转换或非线性/有源材料的情况下，在光子系统中实现非线性计算仍然具有挑战性，而这两种方式都能耗巨大。在此，我们提出一种用于时间序列处理的非线性计算方法。该方法通过利用腔模与光学相位编码输入信号之间的相互作用，能够在单个线性（无源）微腔内对大规模光网络进行节能且非线性的计算，并有助于在硅光子平台上进行片上实现。我们通过实验展示了使用硅光子微腔的高阶非线性计算能力，在诸如混沌时间序列预测和非线性观测器任务等与时间相关的处理任务中实现了卓越性能。
