Improving the machine learning based vertex reconstruction for large liquid scintillator detectors with multiple types of PMTs

Precise vertex reconstruction is essential for large liquid scintillator detectors. A novel method based on machine learning has been successfully developed to reconstruct the event vertex in JUNO previously. In this paper, the performance of machine learning based vertex reconstruction is further i...

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Main Authors Li, Zi-Yuan, Qian, Zhen, He, Jie-Han, He, Wei, Wu, Cheng-Xin, Cai, Xun-Ye, You, Zheng-Yun, Zhang, Yu-Mei, Luo, Wu-Ming
Format Journal Article
LanguageEnglish
Published 09.05.2022
Subjects
Physics - High Energy Physics - Experiment
Physics - Instrumentation and Detectors
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Summary:Precise vertex reconstruction is essential for large liquid scintillator detectors. A novel method based on machine learning has been successfully developed to reconstruct the event vertex in JUNO previously. In this paper, the performance of machine learning based vertex reconstruction is further improved by optimizing the input images of the neural networks. By separating the information of different types of PMTs as well as adding the information of the second hit of PMTs, the vertex resolution is improved by about 9.4 % at 1 MeV and 9.8 % at 11 MeV, respectively.
DOI:10.48550/arxiv.2205.04039