We propose an innovative design for an optical Echo State Network (ESN), an advanced type of reservoir computer known for its universal computational capabilities. Our design enables an optical implementation of arbitrary ESNs, featuring flexibility in optical matrix multiplication and nonlinear activation. Leveraging the nonlinear characteristics of stimulated Brillouin scattering (SBS), the architecture efficiently realizes measurement-free nonlinear activation. The approach significantly reduces computational overhead and energy consumption compared to traditional software-based methods. Comprehensive simulations validate the system's memory capacity, nonlinear processing strength, and polynomial algebra capabilities, showcasing performance comparable to software ESNs across key benchmark tasks. Our design establishes a feasible, scalable, and universally applicable framework for optical reservoir computing, suitable for diverse machine learning applications.

翻译：我们提出了一种创新的光学回声状态网络（ESN）设计，这是一种以其通用计算能力而闻名的高级储层计算机。我们的设计实现了任意ESN的光学实现，具有光学矩阵乘法和非线性激活的灵活性。利用受激布里渊散射（SBS）的非线性特性，该架构高效地实现了无测量的非线性激活。与传统基于软件的方法相比，该方法显著降低了计算开销和能耗。全面的仿真验证了系统的记忆容量、非线性处理能力和多项式代数能力，在关键基准任务中展示了与软件ESN相当的性能。我们的设计为光学储层计算建立了一个可行、可扩展且普遍适用的框架，适用于多种机器学习应用。