Phase control method for generating orbital angular momentum beams using coherent beam combining based on deep...

Area of Science:

• Optics and Photonics
• Laser Physics
• Optical Communications

Background:

• Orbital angular momentum (OAM) beams are crucial for advanced applications like laser communication and optical imaging.
• High-power, high-quality vortex beams are essential for long-distance free-space optical communication.
• Coherent beam combining (CBC) enhances power while preserving beam quality, but rapid phase locking remains a challenge.

Purpose of the Study:

• To develop an efficient method for rapid phase locking of vortex beams in high-power optical systems.
• To overcome limitations of traditional phase control methods in laser phased arrays.
• To improve the capacity and reliability of free-space optical communication using OAM beams.

Main Methods:

• A deep learning approach utilizing spiral phase modulation was proposed.
• A specialized loss function was designed to eliminate phase periodicity, creating a nonlinear mapping.
• A power-in-the-bucket (PIB) metric was introduced to enhance phase prediction accuracy and mitigate dynamic phase errors.

Main Results:

• The deep learning model successfully established a nonlinear mapping between sub-beam phases and far-field images.
• The PIB metric effectively mitigated dynamic phase errors, improving phase prediction accuracy.
• The proposed method demonstrates potential for high-power vortex beam generation and coherent combining.

Conclusions:

• The deep learning-based method offers a promising solution for precise phase control in OAM beam systems.
• This technique can significantly enhance the performance of high-power vortex beam optical systems, particularly those employing coherent combining.
• The findings contribute to advancing free-space optical communication and other OAM-based technologies.