Applications of Machine Learning to Hadron Physics Data Analysis

杰斐逊实验室的CLAS12实验已经开始获取数据，这些数据将被用来寻找奇异介子的证据。这些态的量子数不可能与简单的夸克-反夸克组态相关联，它们的明确发现将为我们提供对包括禁闭在内的强核力特征的关键洞察。该项目将集中开发数据分析方法，包括可能使用机器学习。

The CLAS12 experiment at Jefferson Lab has started to take data that will be used, among other topics, to search for evidence of exotic mesons. These are states that possess quantum numbers that cannot be associated with a simple quark-antiquark configuration, and their unambiguous discovery will provide crucial insight into the characteristics of the strong nuclear force, including confinement. This project will concentrate on the development of data analysis methodologies, including the possible use of machine learning.