Nonlinear germanium-silicon photodiode for activation and monitoring in photonic neuromorphic networks.

ABSTRACT: Silicon photonics is promising for artificial neural networks computing owing to its superior interconnect bandwidth, low energy consumption and scalable fabrication. However, the lack of silicon-integrated and monitorable optical neurons limits its revolution in large-scale artificial neural networks. Here, we highlight nonlinear germanium-silicon photodiodes to construct on-chip optical neurons and a self-monitored all-optical neural network. With specifically engineered optical-to-optical and optical-to-electrical responses, the proposed neuron merges the all-optical activation and non-intrusive monitoring functions in a compact footprint of 4.3 × 8 μm². Experimentally, a scalable three-layer photonic neural network enables in situ training and learning in object classificati

SUBMITTER: Shi Y 

PROVIDER: S-EPMC9561110 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature