Photonic edge intelligence chip for multi-modal sensing, inference and learning.

ABSTRACT: Edge computing requires real-time processing of high-throughput analog signals, posing a major challenge to conventional electronics. Although integrated photonics offers low-latency processing, it struggles to directly handle raw analog data. Here, we present a photonic edge intelligence chip (PEIC) that fuses multiple analog modalities-images, spectra, and radio-frequency signals-into broad optical spectra for single-fiber input. After transmission onto the chip, these spectral inputs are processed by an arrayed waveguide grating (AWG) that performs both spectral sensing and energy-efficient convolution (29 fJ/OP). A subsequent nonlinear activation layer and a fully connected layer form an end-to-end optical neural network, achieving on-chip inference with a measured response time of 1.3

SUBMITTER: Zhang S 

PROVIDER: S-EPMC12630690 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature