Experimental Verification of a Convolutional Neural Network Separation Method in TeV Gamma-Ray Observations by the Tibet ASγ Experiment
Year: 2025
Type: article
Abstract: Since 1990, the Tibet AS$\gamma$ experiment has been observing gamma rays and cosmic rays with energies greater than several TeV using a surface air shower array. An underground muon detector (MD) array operating since 2014 enables us to significantly discriminate between gamma rays and cosmic rays by counting the number of muons in the air showers. However, discrimination with only the air shower array is challenging. We developed a convolutional neural network (CNN)-based method to improve the sensitivity of gamma-ray measurement data recorded by only the air shower array. The area-under-the-curve values of the CNN method for gamma rays generated by a Monte Carlo (MC) simulation assuming a gamma-ray source (Crab Nebula) were 0.75 at $\sim$10 TeV and 0.83 at $\sim$100 TeV. The detection significances of gamma rays were improved by factors of 1.232 $\pm$ 0.007 at $\sim$10 TeV and 1.557 $\pm$ 0.022 at $\sim$100 TeV. For verification, we applied the proposed method to experimental data including high-purity gamma-ray-like events in the direction of the Crab Nebula, acquired using both arrays. The distributions of gamma-ray-like properties obtained from the CNN were in good agreement with the MC Simulation, with reduced $\chi ^2$ values of 0.507–1.57, corresponding to an upper cumulative probability of 0.120–0.871.
DOI: 10.1093/ptep/ptaf127
Authors: M Amenomori, M Anzorena, Y W Bao, X J Bi, D Chen, T L Chen, W Y Chen, Xu Chen, Y Chen, Cirennima, S W Cui, Danzengluobu, L K Ding, J H Fang, K Fang, C F Feng, Y L Feng, Zhaoyang Feng, Z Y Feng, K Fujita, Qi Gao, R Garcia, Q B Gou, Y Q Guo, Y Y Guo, C Y Han, Y Hayashi, H H He, Z T He, K Hibino, N Hotta, Haibing Hu, H B Hu, K Y Hu, J Huang, G Imaizumi, H Y Jia, L Jiang, P Jiang, H B Jin, K Kasahara, Y Katayose, C Kato, S Kato, T Kawashima, K Kawata, M Kozai, Labaciren, G M Le, A F Li, H J Li, W J Li, Y Li, Y H Lin, B Liu, C Liu, J S Liu, L Y Liu, M Y Liu, W Liu, H Lu, T Makishima, Y Masuda, S Matsuhashi, M Matsumoto, X R Meng, Y Meng, A Mizuno, K Munakata, Y Nakamura, H Nanjo, C C Ning, M Nishizawa, Y Noguchi, M Ohnishi, S Okukawa, S Ozawa, X Qian, X L Qian, X B Qu, T Saito, M Sakata, T Sako, T K Sako, J Shao, Q Q Shi, T Shibasaki, M Shibata, A Shiomi, F Sugimoto, H Sugimoto, W Takano, M Takita, Y H Tan, N Tateyama, S Torii, H Tsuchiya, S Udo, R Usui, H Wang, S Wang, S F Wang, Y P Wang, Wangdui, H R Wu, Q Wu, J L Xu, L Xue, G Yamagishi, Z Yang, Y Q Yao, J Yin, Y Yokoe, Y L Yu, A F Yuan, L M Zhai, H M Zhang, J L Zhang, X Zhang, X Y Zhang, Y Zhang, Yi Zhang, Ying Zhang, S P Zhao, Zhaxisangzhu, X X Zhou, Y H Zhou, K Hara
Institutions: Hirosaki University, Institute for Cosmic Ray Research, The University of Tokyo, Nanjing University, Chinese Academy of Sciences, Institute of High Energy Physics, National Astronomical Observatories, Tibet University, Hebei Normal University, University of Chinese Academy of Sciences, Shandong University, Southwest Jiaotong University, Shinshu University, Kanagawa University, Utsunomiya University, Shibaura Institute of Technology, Yokohama National University, Centre National de la Recherche Scientifique, Institut d'Astrophysique de Paris, Sorbonne Université, Research Organization of Information and Systems, Joint Support-Center for Data Science Research, China Meteorological Administration, Shandong Agricultural University, University of Science and Technology of China, National Institute of Informatics, National Institute of Information and Communications Technology, Shandong Management University, China University of Petroleum, East China, Tokyo Metropolitan College of Industrial Technology, Konan University, Nagano Prefectural Institute of Technology, Nihon University, Shonan Institute of Technology, Waseda University, Waseda Research Institute for Science and Engineering, Japan Atomic Energy Agency, Purple Mountain Observatory
Language: English
Subfield: Nuclear and High Energy Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $979
Funders: Ministry of Education, Culture, Sports, Science and Technology, National Natural Science Foundation of China, Chinese Academy of Sciences, Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, University of Tokyo, Japan Society for the Promotion of Science, Institute of High Energy Physics, Institute for Cosmic Ray Research, University of Tokyo
OpenAlex ID: W4415548461