Opt Lett. 2023 Mar 1;48(5):1236-1239. doi: 10.1364/OL.480874.
Chaotic time series prediction has been paid intense attention in recent years due to its important applications. Herein, we present a single-node photonic reservoir computing approach to forecasting the chaotic behavior of external cavity semiconductor lasers using only observed data. In the reservoir, we employ a semiconductor laser with delay as the sole nonlinear physical node. By investigating the effect of the reservoir meta-parameters on the prediction performance, we numerically demonstrate that there exists an optimal meta-parameter space for forecasting optical-feedback-induced chaos. Simulation results demonstrate that using our method, the upcoming chaotic time series can be continuously predicted for a time period in excess of 2 ns with a normalized mean squared error lower than 0.1. This proposed method only utilizes simple nonlinear semiconductor lasers and thus offers a hardware-friendly approach for complex chaos prediction. In addition, this work may provide a roadmap for the meta-parameter selection of a delay-based photonic reservoir to obtain optimal prediction performance.
由于其重要的应用，混沌时间序列预测近年来受到了广泛关注。在此，我们提出了一种单节点光子储层计算方法，仅使用观测数据预测外腔半导体激光器的混沌行为。在储层中，我们采用具有延迟的半导体激光器作为唯一的非线性物理节点。通过研究储层元参数对预测性能的影响，我们数值证明了存在一个最优的元参数空间来预测光反馈诱导的混沌。模拟结果表明，使用我们的方法，可以用归一化均方误差低于 0.1 的数值连续预测超过 2 ns 的时间内的未来混沌时间序列。该方法仅利用简单的非线性半导体激光器，因此为复杂的混沌预测提供了一种硬件友好的方法。此外，这项工作可能为基于延迟的光子储层的元参数选择提供了一条获得最佳预测性能的途径。
