机器学习在大型粒子加速器中的应用回顾与展望  

Machine learning applications in large particle accelerator facilities:review and prospects

作　　者：万金宇 孙正 张相 白宇 蔡承颖 储中明 黄森林[5] 焦毅[1,2] 冷用斌 李标斌 李京祎 李楠 卢晓含[1,2,7] 孟才 彭月梅 王生[1,2,7] 张成艺 Wan Jinyu;Sun Zheng;Zhang Xiang;Bai Yu;Tsai Chengying;Chu Paul;Huang Senlin;Jiao Yi;Leng Yongbin;Li Biaobin;Li Jingyi;Li Nan;Lu Xiaohan;Meng Cai;Peng Yuemei;Wang Sheng;Zhang Chengyi(Institute of High Energy Physics,Chinese Academy of Sciences,Beijing 100049,China;University of Chinese Academy of Sciences,Beijing 100049,China;School of Electrical and Electronic Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;College of Engineering and Applied Science,Nanjing University,Nanjing 210023,China;Institute of Heavy Ion Physics&State Key Laboratory of Nuclear Physics and Technology,Peking University,Beijing 100871,China;Shanghai Advanced Research Institute,Chinese Academy of Sciences,Shanghai 201204,China;China Spallation Neutron Source,Dongguan Guangdong 523803,China)

机构地区：[1]中国科学院高能物理研究所,北京100049 [2]中国科学院大学,北京100049 [3]华中科技大学电气与电子工程学院,武汉430074 [4]南京大学现代工程与应用科学学院,南京210023 [5]北京大学重离子物理研究所&核物理与核技术国家重点实验室,北京100871 [6]中国科学院上海高等研究院,上海201204 [7]散裂中子源科学中心,广东东莞523803

出　　处：《强激光与粒子束》2021年第9期92-106,共15页High Power Laser and Particle Beams

基　　金：国家自然科学基金项目(11922512);中国科学院青年创新促进会项目(Y201904);国家重点研发计划项目(2016YFA0401900)。

摘　　要：机器学习技术在近十几年发展迅猛,并被广泛地用于解决复杂的科学和工程问题。最近十年间,基于机器学习的粒子加速器相关研究也开始呈现出井喷式发展趋势。国际上许多加速器实验室开始尝试用机器学习和大数据技术处理加速器中的海量复杂数据,以期解决加速器及其子系统中的诸多物理和技术问题。不过,迄今为止,机器学习在加速器中的应用仍处于初步探索阶段,不同机器学习算法在解决具体加速器问题的效果及其适用范围尚待摸索,机器学习在实际加速器中的应用仍非常有限。因此,有必要对加速器领域中的机器学习研究做一个整体回顾和总结。将回顾机器学习在大型粒子加速器(以储存环加速器和直线加速器为主)中的加速器技术、束流物理以及加速器整体性能优化等研究方向中已取得的研究成果,并探讨机器学习在加速器领域的未来发展方向和应用前景。Rapid growth of machine learning techniques has arisen over last decades,which results in wide applications of machine learning for solving various complex problems in science and engineering.In the last decade,machine learning and big data techniques have been widely applied to the domain of particle accelerators and a growing number of results have been reported.Several particle accelerator laboratories around the world have been starting to explore the potential of machine learning the processing the massive data of accelerators and to tried to solve complex practical problems in accelerators with the aids of machine learning.Nevertheless,current exploration of machine learning application in accelerators is still in a preliminary stage.The effectiveness and limitations of different machine learning algorithms in solving different accelerator problems have not been thoroughly investigated,which limits the further applications of machine learning in actual accelerators.Therefore,it is necessary to review and summarize the developments of machine learning so far in the accelerator field.This paper mainly reviews the successful applications of machine learning in large accelerator facilities,covering the research areas of accelerator technology,beam physics,and accelerator performance optimization,and discusses the future developments and possible applications of machine learning in the accelerator field.

关 键 词：机器学习 粒子加速器 大科学装置 大数据 加速器技术 束流物理 

分 类 号：TL5[核科学技术—核技术及应用]