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深度神经网络算法在 BESIII 上的应用

创建于2024年01月03日 星期三作者 : 李萍 浏览量 :

主讲人:宋昀轩,瑞士洛桑联邦理工学院(EPFL)博士后

时  间: 2024 年 1 月 5 日 10:00

地  点:物电学院A栋414

联系人:张书磊



讲座摘要:This talk will focus on the application of Graph Neural Networks (GNNs) in particle physics analysis at BESIII. It will explore their effectiveness in studying charmed baryon semileptonic decays and hadronic decays, leveraging the power of GNNs to analyze data with complex relational structures. We will also try to discuss the systematic uncertainty treatment, which is still an open question in experimental particle physic. Finally, this talk also showcases the promise of GNNs in advancing physics analysis at BESIII and lays the foundation for further integration of these techniques in future research



主讲人简介:宋昀轩,瑞士洛桑联邦理工学院(EPFL)博士后。2022 年毕业于北京大学,并获得 BESIII 优秀 博士论文奖。目前在 LHCb 和 BESIII 从事科研工作。主要研究方向为粲物理,奇特强子态,稀有衰变。


深度神经网络算法在 BESIII 上的应用

2024-01-03

作者:宋昀轩

浏览量:

主讲人:宋昀轩,瑞士洛桑联邦理工学院(EPFL)博士后

时  间: 2024 年 1 月 5 日 10:00

地  点:物电学院A栋414

联系人:张书磊



讲座摘要:This talk will focus on the application of Graph Neural Networks (GNNs) in particle physics analysis at BESIII. It will explore their effectiveness in studying charmed baryon semileptonic decays and hadronic decays, leveraging the power of GNNs to analyze data with complex relational structures. We will also try to discuss the systematic uncertainty treatment, which is still an open question in experimental particle physic. Finally, this talk also showcases the promise of GNNs in advancing physics analysis at BESIII and lays the foundation for further integration of these techniques in future research



主讲人简介:宋昀轩,瑞士洛桑联邦理工学院(EPFL)博士后。2022 年毕业于北京大学,并获得 BESIII 优秀 博士论文奖。目前在 LHCb 和 BESIII 从事科研工作。主要研究方向为粲物理,奇特强子态,稀有衰变。


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