Generation of the flat-top beam using convolutional neural networks and Gerchberg-Saxton algorithm

• DOI: 10.1088/1402-4896/ad8d21
• Publication Date: 2024-10-30T22:56:13Z
• Authors: Long Ma; Wei Zhang; Xiangguang Dai
• Keywords: 0103 physical sciences; 0210 nano-technology

Abstract Laser technology has made rapid progress in recent years and been widely used various fields such as medicine, biology, military, materials science. However, the limitations of traditional Gaussian intensity distribution laser beams applications have prompted emergence development flat-top beam shaping technology, which received widespread attention. Here, we introduce a new method for generating that combines Gerchberg-Saxton algorithm with convolutional neural networks, using spatial light modulators to achieve shaping. A comparative analysis was conducted by comparing root mean square error diffraction efficiency generated results obtained only algorithm. Compared algorithm, proposed this paper can generate smaller differences from target higher energy utilization, providing possibilities application technology.