Journal Article Epublish
PubMed: 40487444 DOI: 10.1016/j.isci.2025.112596
Improved all photonics diffraction neural network based on multi-channel integrated optical fibers.
iScience 28(6):112596
Authors: Jiakang Zhu, Qichang An, Fei Yang
Affiliations
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China. University of Chinese Academy of Sciences, Beijing 100039, China.
- Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.
Abstract
AI's exponentially growing computational demands conflict with slow hardware advances. The high-power consumption and long training times of large-scale models call for alternative solutions. Optical computing-based traditional optical networks and diffractive deep neural network (D 2NN) 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.
MeSH
Optical Fibers, Multiple Chronic Conditions