摘要
The precise vertex reconstruction for large liquid scintillator detectors is essential.A novel machine learning-based method was successfully developed to reconstruct an event vertex in JUNO.In this study,the performance of machine learning-based vertex reconstruction was further improved by optimizing the input images of neural networks.By separating the information of different types of PMTs and adding the information of the second hit of PMTs,the vertex resolution was improved by approximately 9.4% at 1 MeV and 9.8% at 11 MeV.
基金
supported by the National Natural Science Foundation of China(Nos.11975021,12175257,12175321,11675275,and U1932101)
the Guangdong Basic and Applied Basic Research Foundation(No.2021A1515012039)
the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)
the National College Students Science and Technology Innovation Project
the Undergraduate Base Scientific Research Project of Sun Yat-sen University
the CAS Center for Excellence in Particle Physics(CCEPP).
