Big Data and AI for High Energy Physics

doi:10.11871/jfdc.issn.2096-742X.2023.02.004

Abstract

Abstract:

[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.

Key words: high energy physics, synchrotron radiation facility, neutron source, big data, artificial intelligence

QI Fazhi,LI Gang,LI Chun,WANG Lu,ZHANG Yi,ZHANG Zhengde,CHEN Gang,LUO Wuming,ZHAO Lina,HU Yu,YUAN Ye. Big Data and AI for High Energy Physics[J]. Frontiers of Data and Computing, 2023, 5(2): 50-59, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2023.02.004.

Figures/Tables 3

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