Improved all photonics diffraction neural network based on multi-channel integrated optical fibers
Year: 2025
Type: article
Abstract: NN) still face deployment challenges and reliance on electronic networks. To address these issues, we replace the free-space interlayer propagation in conventional optical networks with fiber-based propagation. This preserves the advantages of traditional optical networks while providing additional benefits such as ease of deployment, reduced dependence on electronic networks, and enhanced robustness. Experimental results demonstrate that this untrained structure exhibits strong nonlinear mapping capabilities across different configurations, yielding distinct outputs for three input targets, especially at 1550 nm. Furthermore, the influence of environment and noise is around 1% in target recognition. Leveraging inherent spectral discrimination, this architecture enables multidimensional target identification with important implications for complex target classification and multidimensional sensing.
Source: iScience
Authors: Jiakang Zhu, Qichang An, Fei Yang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,240
Funders: National Natural Science Foundation of China, Chinese Academy of Sciences, Department of Science and Technology of Jilin Province, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, National Key Research and Development Program of China, Youth Innovation Promotion Association
OpenAlex ID: W4410119539