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<p>In atmospheric optical communication channels, vortex beams transmitting information through the orbital angular momentum (OAM), are associated with the turbulent atmosphere. While propagating in a&#xa0;turbulent atmosphere, the transmitting laser beam undergoes a&#xa0;random phase distortion leading to errors in the OAM decoding and a&#xa0;decrease in the data transfer rate. In the last years, neural networks have been actively used for the OAM decoding in the turbulent atmosphere. The most common approach is to recognize the OAM specified in the initial plane from the turbulence-distorted instantaneous intensity distribution in the receiving plane. This approach allows mitigating the turbulence effect. Our recent work demonstrates a&#xa0;recognition of opposite-sign OAMs using this approach. It is previously assumed that the OAM sign cannot be retrieved from the instantaneous intensity distribution. This paper analyzes features of intensity distributions of vortex beams in a&#xa0;regular refractive medium that characterizes the OAM sign. It is suggested that the revealed features allow neural networks to determine opposite-sign OAMs through the instantaneous intensity distribution in the turbulent atmosphere.</p>

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Features of intensity distributions of vortex beams in a refractive medium that characterize the sign of the orbital angular momentum

  • 期刊论文

  • 发表日期：

    2025年7月1日

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  • E. A. Bogach,
  • E. V. Adamov,
  • V. V. Dudorov,
  • V. V. Kolosov

摘要

In atmospheric optical communication channels, vortex beams transmitting information through the orbital angular momentum (OAM), are associated with the turbulent atmosphere. While propagating in a turbulent atmosphere, the transmitting laser beam undergoes a random phase distortion leading to errors in the OAM decoding and a decrease in the data transfer rate. In the last years, neural networks have been actively used for the OAM decoding in the turbulent atmosphere. The most common approach is to recognize the OAM specified in the initial plane from the turbulence-distorted instantaneous intensity distribution in the receiving plane. This approach allows mitigating the turbulence effect. Our recent work demonstrates a recognition of opposite-sign OAMs using this approach. It is previously assumed that the OAM sign cannot be retrieved from the instantaneous intensity distribution. This paper analyzes features of intensity distributions of vortex beams in a regular refractive medium that characterizes the OAM sign. It is suggested that the revealed features allow neural networks to determine opposite-sign OAMs through the instantaneous intensity distribution in the turbulent atmosphere.