A reinforced reservoir computer aided by an external asymmetric dual-path-filtering cavity laser

Chaos, characterized by irregular, stochastic-like and occurring in deterministic systems, is widely used in meteorology, life sciences, and physics . Precise chaos predictions are crucial for early warning of extreme weather and disease prevention. We propose a photonic time-delay reservoir computing (TDRC) system with asymmetric dual-path filtering optical feedback under optical injection for short-term prediction of chaotic time series. To thoroughly evaluate the performance in short-term prediction provided by such TDRC, we assess two different chaotic time series, i.e., the Santa-Fe and Mackey-Glass chaotic time series, as well as the memory capacity. Numerical results indicate that the proposed TDRC outperforms the system with conventional dual-path optical feedback in short-term prediction performance. This is attributed to the enhanced memory capacity originating from the asymmetric dual-path filtering optical feedback. Additionally, we reveal the effects of the injection strength , feedback strength, filter bandwidth and the number of virtual nodes on the system performance . Our work provides a novel path for accurate short-term prediction of complex chaotic systems using photonic TDRC. • Introduced an asymmetric dual-path filtering feedback to enhance memory in reservoir computing. • Achieved superior multi-step chaotic time series prediction with enhanced memory capacity. • Identified filtering bandwidth's impact on the performance of reservoir computing.