Vortex beam modal identification system and method based on photonic neural network

Abstract

The invention discloses a vortex beam modal identification system and method based on a photonic neural network. The device comprises: a light beam generation device used for processing stray polarization fundamental mode Gaussian light into a horizontally polarized modal vortex light beam; the characteristic sample preparation device that is used for processing the vortex light beam to obtain a distortion characteristic sample required by waveguide photon neural network training and testing; and the photonic neural network training and recognition simulation device that is used for inputtingthe training set distortion characteristic sample into the waveguide photonic neural network to obtain an optimal model, and performing vortex beam recognition detection on test set data by using theoptimal model; and the waveguide photonic neural network experimental device that is used for loading the phase information in the optimal model to the Mach-Zehnder interferometer array to form a planar waveguide photonic neural network, and is used for vortex beam modal identification in experiments. The invention provides an integrated, efficient and high-speed waveguide photonic neural networkfor vortex beam identification, thereby improving the performance of an OAM communication system.

Description

technical field [0001] The present invention relates to the fields of artificial intelligence and optical technology, in particular to a system and method for modal recognition of vortex beams based on photon neural network. Background technique [0002] Vortex light is a light beam carrying orbital angular momentum OAM (Orbital Angular Momentum, OAM, the angular momentum of moving in space). There is a phase singularity in the center of the beam, and it has a "doughnut" structure in the spatial distribution. These properties make vortex light widely used in optical manipulation, quantum information processing, photonic computer, and free-light space communication. In the field of communication, since different OAM beams are orthogonal to each other, a new physical dimension is provided, which can be combined with traditional multiplexing technology as a carrier for multiplexing, which greatly improves the communication capacity and spectrum efficiency of the system. Due to...

AI Technical Summary

Problems solved by technology

Although deep learning technology can accurately identify OAM modes through image processing, the deep learning technology based on electronic computers is limited by the von Neumann structure, and the information processing speed and energy utilization efficiency are limited.

In addition, the traditional electronic neural network cannot realize all-optical information processing, and often requires photoelectric conversion devices, which cannot further improve the communication capacity and spectral efficiency in OAM multiplexing communication

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