门控循环网络辨识准分子激光器能量模型  

Recognition of Energy Model of Excimer Laser by Gate Recurrent Unit

作　　者：冯泽斌 周翊 江锐 韩晓泉 徐向宇[1,3] 刘斌 Feng Zebin;Zhou Yi;Jiang Rui;Han XiaoQuan;Xu Xiangyu;Liu Bin(Institute of Microelectronics of Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China;Beijing RSLaser Opto-Electronics Technology Co.,Ltd.,Beijing 100176,China)

机构地区：[1]中国科学院微电子研究所,北京100029 [2]中国科学院大学,北京100049 [3]北京科益虹源光电技术有限公司技术中心,北京100176

出　　处：《中国激光》2021年第9期28-37,共10页Chinese Journal of Lasers

基　　金：国家科技重大专项(2013ZX022020)。

摘　　要：准分子激光器的放电过程是一个复杂的非线性过程,从而导致基于放电动力学建立的激光器放电能量模型的精度很难达到仿真研究和控制算法设计的需求。通过深度学习的方法,利用门控循环网络辨识准分子激光器放电能量模型。首先基于准分子激光器出光能量特性,选定所建立的门控循环网络的输入。然后根据门控循环神经网络的输入特性和输出特性建立适用于准分子激光器能量模型辨识的神经网络,并介绍了门控循环神经网络训练方法。最后利用实际采集的激光器的能量数据对门控循环神经网络进行训练。实验结果证明,本文所设计的门控循环神经网络收敛,辨识出来的能量模型的最大误差小于1.5%。该方法可以应用于准分子激光器能量模型的辨识。Objective Excimer lasers are widely used in industrial,medical,and scientific fields because of their short wavelength,high power,and narrow line width.Especially rare gas halogen excimer laser,because of its high peak output power,high single pulse energy,and ultraviolet wavelength,has become the main laser source in the semiconductor lithography industry.Its energy is one of the three key parameters(energy,linewidth,and wavelength)of excimer laser for photolithography,which directly determines the processing accuracy,yield,and key dimensions of semiconductor lithography.When studying the energy of an excimer laser,the closer the model approaches the actual law of light output energy,the more conducive to the study.The output energy model of an excimer laser is the basis for studying and controlling the energy characteristics of the laser.Discharge process of excimer laser is a complex nonlinear process,which leads to the accuracy of laser discharge energy model based on discharge dynamics is difficult to meet the needs of simulation research and control algorithm design.In this paper,the method based on deep learning was applied to identify the energy mode of excimer laser to avoid the inaccuracy of theoretical modeling.Methods The development of deep learning theory has become more and more complete.It has become a tool and has been widely applied.Among them,recurrent neural network(RNN)is an important branch in the field of deep learning.It has been widely used in language recognition,machine translation,text analysis and other fields.In recent years,circulating neural networks abroad,especially its variant gate recurrent unit(GRU),has been applied to model recognition,trend prediction and other fields.In this paper,the gated recurrent unit network was used to identify the discharge energy model of the excimer laser.Firstly,based on the characteristics of the excimer laser energy,the discharge voltage and discharge interval were selected as the input of the established gating recurrent unit network.Then,accor

关 键 词：激光器 门控循环单元网络 准分子激光器 模型辨识 

分 类 号：TN248.2[电子电信—物理电子学]