Denoising in Mode Conversion by Utilizing Diffractive Deep Neural Networks Optimized with Reinforcement Learning
Zheng Li, Wenbo Zhang, Yang Wang, Guanju Peng, Zongze Li, Xiaoyan Zhou, Lin Zhang · 2024
We propose a reinforcement-learning-optimized nonlinear physical diffractive neural network, which can simultaneously perform OAM-mode and LP-mode conversion with Gaussian noise removal. The PSNR and SSIM of the converted modes reach 27.94 dB and 0.838, respectively.