Programmable phase-change metasurfaces on waveguides for multimode photonic convolutional neural network.

ABSTRACT: Neuromorphic photonics has recently emerged as a promising hardware accelerator, with significant potential speed and energy advantages over digital electronics for machine learning algorithms, such as neural networks of various types. Integrated photonic networks are particularly powerful in performing analog computing of matrix-vector multiplication (MVM) as they afford unparalleled speed and bandwidth density for data transmission. Incorporating nonvolatile phase-change materials in integrated photonic devices enables indispensable programming and in-memory computing capabilities for on-chip optical computing. Here, we demonstrate a multimode photonic computing core consisting of an array of programable mode converters based on on-waveguide metasurfaces made of phase-change materials. T

SUBMITTER: Wu C 

PROVIDER: S-EPMC7782756 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature