Photonic Neuromorphic Processing With Coupled Spiking Silicon Microrings

Understanding the physical computing mechanisms of individual network nodes is essential for scaling neuromorphic photonic architectures. This work proposes a compact passive nonlinear photonic core based on a side‐coupled integrated spaced sequence of resonators (SCISSOR) comprising three nominally equal microrings and investigate its computing capabilities. Its nonlinearities and internal feedback enable analogue, spiking, and bistable responses that are accessed by tuning the injection power and wavelength. Implemented as a single nonlinear node in a time‐multiplexed reservoir computing, the SCISSOR achieves error‐free classification on the Iris dataset and accuracies above 97 on the Sonar task, using both analogue and digital reservoir representations with 150 virtual nodes. In the digital scheme, spiking dynamics naturally generate sparse reservoir states, enabling efficient classification even with a single spike. Intriguingly, operating points at the boundaries where sharp transitions in dynamical complexity and/or output power occur support high task‐performance, opening novel strategies for future on‐chip training. Spiking and thermal bistabilities also participate to enhance the computational performance. These results suggest that coupled optical microrings can serve as compact, physically interpretable nonlinear building blocks for future neuromorphic photonic processors, particularly in optical‐domain preprocessing and sensing scenarios where kHz‐to‐MHz signal bandwidths are relevant.