Applications of Machine Learning to Hadron Physics Data Analysis

机器学习在强子物理数据分析中的应用

• 批准号: 2370385
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2370385
• 关键词: Applications; Machine; Learning; Hadron; Physics

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.

杰斐逊实验室的CLAS 12实验已经开始收集数据，这些数据将用于寻找奇异介子的证据。这些状态所具有的量子数不能与简单的夸克-反夸克配置相关联，它们的明确发现将为强核力的特征（包括禁闭）提供至关重要的见解。该项目将侧重于开发数据分析方法，包括可能使用机器学习。