Laser & Optoelectronics Progress, Volume. 60, Issue 17, 1703001(2023)

Self-Healing Properties of Twisted Elliptical Gaussian Schell-Model Beams

Yinlong Guo1, Xinyu Nie1, Jinhong Li1, Xianmei Qian2, Wenyue Zhu2, and Jing Wang1、*
Author Affiliations
  • 1School of Applied Science, Taiyuan University of Science and Technology, Taiyuan 030024, Shanxi , China
  • 2Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui , China
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    In this study, the analytical expression of field distribution of twisted elliptical Gaussian Schell-Model beams after they pass through a Gaussian absorption-type obstacle is derived based on the Collins formula, and a basic twisted-beam model is obtained that effectively enhances the beam's self-healing capability. The effects of the light source parameters on the beam's self-healing properties are analyzed. The laws of intensity, coherence, and orbital angular momentum flux density transmitted when partially blocked by obstacles and the intrinsic connection among the three quantities are revealed. The intrinsic self-healing properties of twisted beams are explained. It is shown that appropriately reducing the coherence length and twist factor can enhance the beam's self-healing capability while preserving the characteristics of the twisted beam. The findings can help optimize the overall performance of partially coherent light transmission in free space, thus enhancing potential applications in free space optical communication, LIDAR, remote sensing imaging, and other fields.

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    Yinlong Guo, Xinyu Nie, Jinhong Li, Xianmei Qian, Wenyue Zhu, Jing Wang. Self-Healing Properties of Twisted Elliptical Gaussian Schell-Model Beams[J]. Laser & Optoelectronics Progress, 2023, 60(17): 1703001

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    Paper Information

    Category: COHERENCE OPTICS AND STATISTICAL OPTICS

    Received: Aug. 2, 2022

    Accepted: Sep. 5, 2022

    Published Online: Aug. 29, 2023

    The Author Email: Wang Jing (wangjingtyust@163.com)

    DOI:10.3788/LOP222216

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