Recognition of opposite-sign orbital angular momenta of laser beams in a turbulent atmosphere by neural networks
E.A. Bogach, E.V. Adamov, V.V. Dudorov, V.V. Kolosov
V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of the Russian Academy of Science, Tomsk, Russia
Keywords: orbital angular momentum, topological charge, vortex beam, turbulent atmosphere, optical vortex, neural network
Abstract
Currently, many studies are aimed at increasing the information capacity of data transmission channels by using the orbital angular momentum (OAM) of laser beams to encode information. The use of this approach in atmospheric optical communication systems is limited by the distorting effect of atmospheric turbulence, which makes decoding difficult and reduces the data transfer rate. In addition, the intensity distributions of vortex beams with opposite in sign OAM values are identical in the case of homogeneous media, which limits the use of the OAM sign for encoding information. The main goal of the study was to evaluate the fundamental possibility of using neural networks to recognize opposite in sign OAM values of vortex beams in a turbulent atmosphere only through intensity images. The study is based on numerical simulation of the Laguerre-Gauss beam propagation in a turbulent atmosphere and further use of the obtained intensity images for training and testing neural networks. It has been shown for the first time that the use of neural networks makes it possible to recognize opposite in sign OAM values of Laguerre-Gauss beam through intensity images in case of propagation in a turbulent atmosphere with an accuracy of more than 90%. The obtained results can be useful for developers and researchers of atmospheric optical communication systems using OAM of vortex beam.
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