Using Active Surface Plasmons in a Multibit Optical Storage Device to Emulate Long-Term Synaptic Plasticity

PHYSICA STATUS SOLIDI A-APPLICATIONS AND MATERIALS SCIENCE(2020)

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摘要
Artificial intelligence takes inspiration from the functionalities and structure of the brain to solve complex tasks and allow learning. Yet, hardware realization that simulates the synaptic activities realized with electrical devices still lags behind computer software implementation, which has improved significantly during the past decade. Herein, the capability to emulate synaptic functionalities by exploiting surface plasmon polaritons (SPPs) is shown. By depositing photochromic switching molecules (diarylethene) on a thin film of gold, it is possible to reliably control the electronic configuration of the molecules upon illumination cycles with UV and visible light. These reversible changes modulate the dielectric function of the photochromic film and thus enable the effective control of the SPP dispersion relation at the molecule/gold interface. The plasmonic device displays fundamental functions of a synapse such as potentiation, depression, and long-term plasticity. The integration of such plasmonic devices in an artificial neural network is deployed in plasmonic neuroinspired circuits for optical computing and data transmission.
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关键词
artificial intelligence,long-term plasticities,surface plasmon polaritons,switching molecules
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