基于人工智能的高能物理大数据技术与应用  

Big Data and AI for High Energy Physics

作　　者：齐法制[1] 李刚[1] 李纯 汪璐[1] 张一 张正德 陈刚[1] 罗武鸣 赵丽娜 胡誉 袁野[1] QI Fazhi;LI Gang;LI Chun;WANG Lu;ZHANG Yi;ZHANG Zhengde;CHEN Gang;LUOWuming;ZHAO Lina;HU Yu;YUAN Ye(The Institute of High Energy Physics,Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院高能物理研究所,北京100049

出　　处：《数据与计算发展前沿》2023年第2期50-59,共10页Frontiers of Data & Computing

基　　金：国家高能物理科学数据中心的支持。

摘　　要：【目的】高能物理的科学目标是探索物质微观结构以及相互作用的基本原理,这些研究均依赖于超大规模的高能物理实验装置。由高能物理加速器技术衍生出来的同步辐射光源、自由电子激光、散裂中子源装置成为材料科学、生物医学、环境科学、地质学、物理、化学等学科领域的基础和应用研究的不可替代的工具。新一代高能物理实验装置的规模和复杂度得到巨大的提升,实验产生的数据量出现数量级的增长。人工智能和大数据技术逐步成为应对高能物理装置运行以及数据处理挑战的有效工具,并带来科研范式的变革。【方法】本文讨论了高能物理在大数据方面的挑战、国内外大数据与AI在高能物理领域的应用现状。文章介绍了国内高能物理大数据与AI的战略部署和相关研究,同时介绍了一些应用示范案例。【结论】文章最后对大数据与AI带来的科研范式变革进行了讨论。[Objective]High energy physics is a field of science to explore the elementary constituents of matter,and the interactions between them.Most of the research relies on large experimental infrastructures.The technology developed by high energy physics helped to build useful experimental platforms including synchrotron radiation facilities,free electron laser,and spallation neutron sources which have become important tools of many branches of scientific research including material science,bio-medicine,environmental research,geology,physics,and chemistry.The new generation of high-energy physics creates unprecedented amounts of data which brings people big challenges to deal with.[Methods]In recent years big data and AI have been introduced to high energy physics to attack the challenges.In this work,the status of big data and AI for high energy physics are discussed.[Results]The research activities of big data and AI in the field are introduced.

关 键 词：高能物理 同步辐射装置 中子源 大数据 人工智能 

分 类 号：O572[理学—粒子物理与原子核物理] TP311.13[理学—物理]