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Multiplexable all-optical nonlinear activator for optical computing
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AI
DOI：10.1364/OE.522087.png)
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摘要
En 中文
As an alternative solution to surpass electronic neural networks, optical neural networks (ONNs) offer significant advantages in terms of energy consumption and computing speed. Despite the optical hardware platform could provide an efficient approach to realizing neural network algorithms than traditional hardware, the lack of optical nonlinearity limits the development of ONNs. Here, we proposed and experimentally demonstrated an all -optical nonlinear activator based on the stimulated Brillouin scattering (SBS). Utilizing the exceptional carrier dynamics of SBS, our activator supports two types of nonlinear functions, saturable absorption and rectified linear unit (Relu) models. Moreover, the proposed activator exhibits large dynamic response bandwidth ( similar to 11.24 GHz), low nonlinear threshold ( similar to 2.29 mW), high stability, and wavelength division multiplexing identities. These features have potential advantages for the physical realization of optical nonlinearities. As a proof of concept, we verify the performance of the proposed activator as an ONN nonlinear mapping unit via numerical simulations. Simulation shows that our approach achieves comparable performance to the activation functions commonly used in computers. The proposed approach provides support for the realization of all -optical neural networks.
Keyword:
STIMULATED BRILLOUIN-SCATTERING
NEURAL-NETWORK
EXPERIMENTAL REALIZATION
ARTIFICIAL-INTELLIGENCE