Programmable photonic neural engine with all-optical nonlinear activation and 40,000 connections
2026-08-19
The rapid advancement of artificial neural networks (ANNs) demands computational platforms with higher speed, energy efficiency, and scalability. Optical computing offers an appealing solution owing to the high-speed processing, inherent parallelism, and low energy consumption. However, existing optical neural network architectures face fundamental trade-offs between scalability, reconfigurability, and processing latency, constrained by the need to rely on electronic nonlinearities or fixed optical interconnections. Here, we report an end-to-end photonic neuromorphic engine that integrates all-optical nonlinearity into a loop-based, time-multiplexed photonic architecture. This approach enables all optical neurons to share common hardware, supporting enhanced connectivity and full reconfigurability with reduced latency. Implementations of four distinct network topologies, with a maximum of 40,000 optical connections for the single-layer perceptron, achieve digital-level inference accuracy and computational latency over two orders of magnitude shorter than state-of-the-art electronic processors, potentially paving the way for scalable, reconfigurable, and ultrafast optical artificial intelligence systems.