Vertex and energy reconstruction in JUNO with machine learning methods

Zhen Qian,Vladislav Belavin, Vasily Bokov,Riccardo Brugnera, Alessandro Compagnucci,Arsenii Gavrikov,Alberto Garfagnini,Maxim Gonchar, Leyla Khatbullina,Ziyuan Li,Wuming Luo,Yury Malyshkin, Samuele Piccinelli,Ivan Provilkov,Fedor Ratnikov, Dmitry Selivanov,Konstantin Treskov,Andrey Ustyuzhanin,Francesco Vidaich,Zhengyun You,Yumei Zhang,Jiang Zhu, Francesco Manzali

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment（2021）

引用 21|浏览49

暂无评分

摘要

The Jiangmen Underground Neutrino Observatory (JUNO) is an experiment designed to study neutrino oscillations. Determination of neutrino mass ordering and precise measurement of neutrino oscillation parameters sin2θ12, Δm212 and Δm312 are the main goals of the experiment. A rich physical program beyond the oscillation analysis is also foreseen. The ability to accurately reconstruct particle interaction events in JUNO is of great importance for the success of the experiment.

查看译文

关键词

Machine learning,JUNO,Energy reconstruction,Vertex reconstruction

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要