Abstract
The rich structure of transverse spatial modes of structured light has facilitated their extensive applications in quantum information and optical communication.The Laguerre-Gaussian(LG)modes,which carry a well-defined orbital angular momentum(OAM),consist of a complete orthogonal basis describing the transverse spatial modes of light.The application of OAM in free-space optical communication is restricted due to the experimentally limited OAM numbers and the complex OAM recognition methods.Here,we present a novel method that uses the advanced deep learning technique for LG modes recognition.By discretizing the spatial modes of structured light,we turn the OAM state regression into classification.A proof-of-principle experiment is also performed,showing that our method effectively categorizes OAM states with small training samples and the accuracy exceeds 99％from three-dimensional(3D)to fifteen-dimensional(15D)space.By assigning each category a classical information,we further apply our approach to an image transmission task,achieving a transmission accuracy of 99.58％,which demonstrates the ability to encode large data with low OAM number.This work opens up a new avenue for achieving high-capacity optical communication with low OAM number based on structured light.
维普
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