全息术
计算机科学
加权
梯度下降
算法
平版印刷术
相位恢复
光学
人工智能
物理
人工神经网络
傅里叶变换
声学
量子力学
作者
Haichao Wang,Weirui Yue,Qiang Song,Jingdan Liu,Guohai Situ
标识
DOI:10.1016/j.optlaseng.2016.04.005
摘要
Abstract The Gerchberg–Saxton (GS) algorithm is widely used in various disciplines of modern sciences and technologies where phase retrieval is required. However, this legendary algorithm most likely stagnates after a few iterations. Many efforts have been taken to improve this situation. Here we propose to introduce the strategy of gradient descent and weighting technique to the GS algorithm, and demonstrate it using two examples: design of a diffractive optical element (DOE) to achieve off-axis illumination in lithographic tools, and design of a computer generated hologram (CGH) for holographic display. Both numerical simulation and optical experiments are carried out for demonstration.
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