Conceptual illustration of the OAM-mediated machine learning and the application of all-optical information mode-feature encoding. (IMAGE)

Light Publishing Center, Changchun Institute of Optics, Fine Mechanics And Physics, CAS

Conceptual illustration of the OAM-mediated machine learning and the application of all-optical information mode-feature encoding.

Caption

a.The architecture of the all-optical CNN for OAM-mediated machine learning, which can be applied to encode a data-specific image into OAM states. The photonic neural network comprises a trainable convolutional layer which can provide an OAM mode-dispersion impulse to densify the input OAM mode comb and extract the feature, and successive phase-engineered diffractive layers with finite size as a classifier to reduce the dense OAM mode spectrum to a couple of target terms due to the OAM mode-dispersion selectivity. B. The proposed CNN with an appropriate OAM modes decoder/demultiplexer can be applied in, image classification, and all-optical abnormal detection, respectively.

Credit

by Xinyuan Fang, Xiaonan Hu, Baoli Li, Hang Su, Ke Cheng, Haitao Luan, and Min Gu

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Credit must be given to the creator.

License

CC BY

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