Journal: Light, Science & Applications
Article Title: Optical neural networks: progress and challenges
doi: 10.1038/s41377-024-01590-3
Figure Lengend Snippet: ONNs constructed by MZIs. a On-chip ONN based on 56 MZIs . b Mathematical inference diagram of the training process for ONN that supports in-situ online training . c On-chip ONNs based on amplitude and phase modulation . d ONN chip designed and fabricated based on MZIs and diffractive units . a Reproduced from ref. with permission of Springer Nature: Nature Photonics. b Reproduced with permission from ref. from © Optical Society of America. c Reproduced from ref. with permission of Springer Nature: Nature Communications. d Reproduced from ref. with permission of Springer Nature: Nature Communications
Article Snippet: Fig. 10 ONNs constructed by MZIs. a On-chip ONN based on 56 MZIs . b Mathematical inference diagram of the training process for ONN that supports in-situ online training . c On-chip ONNs based on amplitude and phase modulation . d ONN chip designed and fabricated based on MZIs and diffractive units . a Reproduced from ref. with permission of Springer Nature: Nature Photonics. b Reproduced with permission from ref. from © Optical Society of America. c Reproduced from ref. with permission of Springer Nature: Nature Communications. d Reproduced from ref. with permission of Springer Nature: Nature Communications In 2021, Zhang et al. pointed out that most research on ONNs still only uses traditional real-value frameworks designed for digital computers.
Techniques: Construct, In Situ