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Reconstruction of Cherenkov image bymultiple telescopes of LHAASO-WFCTA

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Radiation Detection Technology and Methods 2022年第4期6卷 544-557页

作者： F.Aharonian Q.An Axikegu L.X.Bai Y.X.Bai Y.W.Bao D.Bastieri X.J.Bi Y.J.Bi J.T.Cai Zhe Cao Zhen Cao J.Chang J.F.Chang E.S.Chen Liang Chen Liang Chen Long Chen M.J.Chen M.L.Chen Q.H.Chen S.H.Chen S.Z.Chen T.L.Chen Y.Chen H.L.Cheng N.Cheng Y.D.Cheng S.W.Cui X.H.Cui Y.D.Cui B.D’Ettorre Piazzoli B.Z.Dai H.L.Dai Z.G.Dai Danzengluobu Ddella Volpe K.K.Duan J.H.Fan Y.Z.Fan Z.X.Fan J.Fang K.Fang C.F.Feng L.Feng S.H.Feng X.T.Feng Y.L.Feng B.Gao C.D.Gao L.Q.Gao Q.Gao W.Gao W.K.Gao M.M.Ge L.S.Geng G.H.Gong Q.B.Gou M.H.Gu F.L.Guo J.G.Guo X.L.Guo Y.Q.Guo Y.Y.Guo Y.A.Han H.H.He H.N.He S.L.He X.B.He Y.He M.Heller Y.K.Hor C.Hou X.Hou H.B.Hu Q.Hu S.Hu S.C.Hu X.J.Hu D.H.Huang W.H.Huang X.T.Huang X.Y.Huang Y.Huang Z.C.Huang X.L.Ji H.Y.Jia K.Jia K.Jiang Z.J.Jiang M.Jin M.M.Kang T.Ke D.Kuleshov K.Levochkin B.B.Li Cheng Li Cong Li F.Li H.B.Li H.C.Li H.Y.Li J.Li Jian Li Jie Li K.Li WLLi XRLi Xin Li Xin Li YZLi Zhe Li Zhuo Li E.W.Liang Y.F.Liang S.J.Lin B.Liu C.Liu D.Liu H.Liu H.D.Liu J.Liu J.L.Liu J.S.Liu J.Y.Liu M.Y.Liu R.Y.Liu S.M.Liu W.Liu Y.Liu Y.N.Liu W.J.Long R.Lu Q.Luo H.K.Lv B.Q.Ma L.L.Ma X.H.Ma J.R.Mao A.Masood Z.Min W.Mitthumsiri Y.C.Nan Z.W.Ou B.Y.Pang P.Pattarakijwanich Z.Y.Pei M.Y.Qi Y.Q.Qi B.Q.Qiao J.J.Qin D.Ruffolo A.Sáiz C.Y.Shao L.Shao O.Shchegolev X.D.Sheng J.Y.Shi H.C.Song Yu.V.Stenkin V.Stepanov Y.Su Q.N.Sun X.N.Sun Z.B.Sun P.H.T.Tam Z.B.Tang W.W.Tian B.D.Wang C.Wang H.Wang H.G.Wang J.C.Wang J.S.Wang L.P.Wang L.Y.Wang R.Wang R.N.Wang W.Wang X.G.Wang X.Y.Wang Y.Wang Y.D.Wang Y.J.Wang Y.P.Wang Z.H.Wang Z.X.Wang Zhen Wang Zheng Wang D.M.Wei J.J.Wei Y.J.Wei T.Wen C.Y.Wu H.R.Wu S.Wu X.F.Wu Y.S.Wu S.Q.Xi J.Xia J.J.Xia G.M.Xiang D.X.Xiao G.Xiao G.G.Xin Y.L.Xin Y.Xing Z.Xiong D.L.Xu R.X.Xu L.Xue D.H.Yan J.Z.Yan C.W.Yang F.F.Yang H.W.Yang J.Y.Yang L.L.Yang M.J.Yang R.Z.Yang S.B.Yang Y.H.Yao Z.G.Yao Y.M.Ye L.Q.Yin N.Yin X.H.You Z.Y.You Y.H.Yu Q.Yuan H.Yue H.D.Zeng T.X.Zeng W.Zeng Z.K.Zeng M.Zha X.X.Zhai B.B.Zhang F.Zhang H.M.Zhang H.Y.Zhang J.L.Zhang L.X.Zhang Li Zhang Lu Zhang P.F.Zhang P.P.Zhang R.Zhang S.B.Zhang S.R.Zhang S. Key Laboratory of Particle Astrophyics&Experimental Physics Division&Computing Center Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China TIANFU Cosmic Ray Research Center ChengduSichuanChina Dublin Institute for Advanced Studies 31 Fitzwilliam Place2DublinIreland Max-Planck-Institut for Nuclear Physics P.O.Box 10398069029 HeidelbergGermany State Key Laboratory of Particle Detection and Electronics BeijingChina University of Science and Technology of China Hefei 230026AnhuiChina School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031SichuanChina College of Physics Sichuan UniversityChengdu 610065SichuanChina School of Astronomy and Space Science Nanjing UniversityNanjing 210023JiangsuChina Center for Astrophysics Guangzhou UniversityGuangzhou 510006GuangdongChina Key Laboratory of Dark Matter and Space Astronomy&Key Laboratory of Radio Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023JiangsuChina Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Key Laboratory of Cosmic Rays(Tibet University) Ministry of EducationLhasa 850000TibetChina National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China Hebei Normal University Shijiazhuang 050024HebeiChina School of Physics and Astronomy(Zhuhai)&Sino-French Institute of Nuclear Engineering and Technology(Zhuhai) Sun Yat-sen UniversityZhuhai 519000China School of Physics(Guangzhou) Sun Yat-sen UniversityGuangzhou 510275GuangdongChina Dipartimento di Fisica dell’Universitàdi Napoli“Federico II” Complesso Universitario di Monte Sant’Angelovia Cinthia80126 NapoliItaly School of Physics and Astronomy Yunnan UniversityKunming 650091YunnanChina Département de Physique Nucléaire et Corpusculaire Facultéde SciencesUniversitéde Genève

Introduction One of main scientiﬁc goals of the Large High Altitude Air Shower Observatory(LHAASO)is to accurately measure the energy spectra of different cosmic ray compositions around the‘knee’*** Wide Field-of-View(FoV)Cherenkov Telescope Array(WFCTA),which is one of the main detectors of LHAASO and has 18 telescopes,is built to achieve this *** telescopes are put together and point to connected directions for a larger *** Telescopes are deployed spatially as close as possible,but due to their own size,the distance between two adjacent telescopes is about 10 ***,the Cherenkov lateral distribution and the parallax between the two telescopes should be considered in the event building process for images crossing over the boundaries of FoVs of the *** event building method for Cherenkov images measured by multiple telescopes of WFCTA is *** performance of the shower measurements using the combined images is evaluated by comparing with showers that are fully contained by a virtual telescope in *** and conclusion It is proved that the developed event building process can help to increase the FoV of WFCTA by 30%while maintaining the same reconstruction quality,compared to the separate telescope reconstruction method.

关键词： method directions conclusion

Potential Indicator for Continuous Emotion Arousal by Dynamic Neural Synchrony

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arXiv 2025年

作者： Pan, Guandong Wu, Zhaobang Yang, Yaqian Wang, Xin Liu, Longzhao Zheng, Zhiming Tang, Shaoting School of Computer Science and Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Key laboratory of Mathematics Informatics and Behavioral Semantics Beihang University Beijing100191 China Institute of Medical Artificial Intelligence Binzhou Medical University Yantai264003 China Zhongguancun Laboratory Beijing100094 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Beijing100191 China PengCheng Laboratory Shenzhen518055 China State Key Lab of Software Development Environment Beihang University Beijing100191 China

The need for automatic and high-quality emotion annotation is paramount in applications such as continuous emotion recognition and video highlight detection, yet achieving this through manual human annotations is challenging. Inspired by inter-subject correlation (ISC) utilized in neuroscience, this study introduces a novel Electroencephalography (EEG) based ISC methodology that leverages a single-electrode and feature-based dynamic approach. Our contributions are three folds: Firstly, we reidentify two potent emotion features suitable for classifying emotions—first-order difference (FD) an differential entropy (DE). Secondly, through the use of overall correlation analysis, we demonstrate the heterogeneous synchronized performance of electrodes. This performance aligns with neural emotion patterns established in prior studies, thus validating the effectiveness of our approach. Thirdly, by employing a sliding window correlation technique, we showcase the significant consistency of dynamic ISCs across various features or key electrodes in each analyzed film clip. Our findings indicate the method’s reliability in capturing consistent, dynamic shared neural synchrony among individuals, triggered by evocative film stimuli. This underscores the potential of our approach to serve as an indicator of continuous human emotion arousal. The implications of this research are significant for advancements in affective computing and the broader neuroscience field, suggesting a streamlined and effective tool for emotion analysis in real-world applications. © 2025, CC BY-NC-SA.

关键词： Neurons

Persistent photogenerated state attained by femtosecond laser irradiation of thin Td-MoTe2

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arXiv 2022年

作者： Cheng, Meixin Zhong, Shazhou Rivas, Nicolas Dekker, Tina Petruk, Ariel Alcides Gicala, Patrick Pichugin, Kostyantyn Chen, Fangchu Luo, Xuan Sun, Yuping Tsen, Adam W. Sciaini, Germán The Ultrafast Electron Imaging Lab Department of Chemistry Waterloo Institute for Nanotechnology University of Waterloo WaterlooONN2L 3G1 Canada Institute for Quantum Computing Department of Physics and Astronomy Department of Electrical and Computer Engineering Department of Chemistry University of Waterloo WaterlooONN2L 3G1 Canada Key Laboratory of Materials Physics Institute of Solid-State Physics HFIPS Chinese Academy of Sciences Hefei230031 China High Magnetic Field Laboratory Chinese Academy of Sciences HFIPS Hefei230031 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China

Laser excitation has emerged as a means to expose hidden states of matter and promote phase transitions on demand. Such laser induced transformations are often rendered possible owing to the delivery of spatially and/or temporally manipulated light, carrying energy quanta well above the thermal background. Here, we report time-resolved broadband femtosecond (fs) transient absorption measurements on thin flakes of Weyl semimetal candidate Td-MoTe2 subjected to various levels and schemes of fs-photoexcitation. Our results reveal that impulsive fs-laser irradiation alters the interlayer behavior of the low temperature Td phase as evidenced by the persistent disappearance of its characteristic coherent 1A1≈ 13 cm–1 shear phonon mode. We found that this structural transformation withstands thermal annealing up to 500 K, although it can be reverted to the 1T’ phase by fs-laser treatment at room temperature. Our work opens the door to reversible optical control of topological properties. Copyright © 2022, The Authors. All rights reserved.

关键词： Transition metals

Photoinduced Interlayer Dynamics in Td-MoTe2: A Broadband Pump-Probe Study

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arXiv 2022年

作者： Cheng, Meixin Zhong, Shazhou Rivas, Nicolas Dekker, Tina Petruk, Ariel Alcides Gicala, Patrick Pichugin, Kostyantyn Chen, Fangchu Luo, Xuan Sun, Yuping Tsen, Adam W. Sciaini, Germán The Ultrafast electron Imaging Lab. Department of Chemistry Waterloo Institute for Nanotechnology University of Waterloo WaterlooONN2L 3G1 Canada Institute for Quantum Computing Department of Physics and Astronomy Department of Electrical and Computer Engineering Department of Chemistry University of Waterloo WaterlooONN2L 3G1 Canada Key Laboratory of Materials Physics Institute of Solid-State Physics Chinese Academy of Sciences Hefei230031 China High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China

We report on time-resolved broadband transient reflectivity (tr-bb-TR) measurements performed on a bulk single crystal of Td-MoTe2 as a function of the incident pump fluence (F). Tr-bb-TR data unveil photoinduced electronic changes progressing on the sub-picosecond timescale as well as the dynamics of the coherent low-frequency 1A1 interlayer shear phonon. Our results indicate a gradual evolution of both the TR and the 1A1 Fourier intensity spectra as a function of F, ruling out the threshold-like change that has been associated with the ultrafast photoinduced Td ® 1T’ phase transition. We also observe a large redshift of the 1A1 Fourier spectral features, which suggests that large renormalization effects are taking place on interband transitions that are dielectrically susceptible to the 1A1 interlayer phonon displacement. Copyright © 2022, The Authors. All rights reserved.

关键词： Transition metals

Applications of Game Theory in Vehicular Networks: A Survey

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arXiv 2021年

作者： Sun, Zemin Liu, Yanheng Wang, Jian Li, Guofa Anil, Carie Li, Keqiang Guo, Xinyu Sun, Geng Tian, Daxin Cao, Dongpu College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China School of Computer Science and Engineering VIT-AP Andhra Pradesh Amaravati522237 India College of Engineering Nanjing Agricultural University Nanjing210031 China State Key Laboratory of Automotive Safety and Energy Department of Automotive Engineering Tsinghua University Beijing100084 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing100191 China Waterloo Cognitive Autonomous Driving Lab University of Waterloo N2L 3G1 Canada

In the Internet of things (IoT) era, vehicles and other intelligent components in an intelligent transportation system (ITS) are connected, forming vehicular networks (VNs) that provide efficient and safe traffic and ubiquitous access to various applications. However, as the number of nodes in an ITS increases, it is challenging to satisfy a varied and large number of service requests with different quality of service (QoS) and security requirements in highly dynamic VNs. Intelligent nodes in VNs can compete or cooperate for limited network resources to achieve the objective for either an individual or a group. Game theory (GT), a theoretical framework designed for strategic interactions among rational decision makers sharing scarce resources, can be used to model and analyze individual or group behaviors of communicating entities in VNs. This paper primarily surveys the recent developments of GT in solving various challenges of VNs. This survey starts with an introduction to the background of VNs. A review of GT models studied in the VNs is then introduced, including the basic concepts, classifications, and applicable vehicular issues. After discussing the requirements of VNs and the motivation of using GT, a comprehensive literature review on GT applications in dealing with the challenges of current VNs is provided. Furthermore, recent contributions of GT to VNs that are integrated with diverse emerging 5G technologies are surveyed. Finally, the lessons learned are given, and several key research challenges and possible solutions of applying GT in VNs are outlined. Copyright © 2021, The Authors. All rights reserved.

关键词： Quality of service

Vulnerability Fingerprint: An Efficient De-duplicating Technology of Crashes

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Vulnerability Fingerprint: An Efficient De-duplicating Techn...

International Conference on Computer and Communications (ICCC)

作者： Chiheng Wang Jianshan Peng Qingxian Wang Xiaoli Duan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China China United Network Communications Group Co. Ltd Shanxi Yuncheng Branch Yuncheng China

ISBN: (数字)9781728147437

ISBN: (纸本)9781728147444

With the broad application of fuzzing, the efficiency of vulnerability discovery improves, result in a large number of crashes generating more and more rapidly. However, the analysis of the crashes is a highly repetitive manual work. Here, to identify vulnerability features and de-duplicate crashes, a new technology was proposed which we called Vulnerability Fingerprint. We defined the basic vulnerability features of the Vulnerability Fingerprint, and used the multi-level classification method to establish the Vulnerability Fingerprint feature model. Finally, based on the Linux operating system, we designed and implemented the Vulnerability Fingerprint extraction tool, and tested the crashes obtained by fuzzing of real software. The results showed that there was a more than 90% reduction of crashes workload with the Vulnerability Fingerprint. And in the de-duplicated crashes, the vulnerability coverage rate even could reach nearly 100%.

关键词： Computer crashes Fingerprint recognition Instruments Feature extraction Tools Micromechanical devices Registers

Disorder-induced pronounced magnetoresistive hysteresis in Josephson junctions

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Physical Review B 2025年第13期111卷 134513-134513页

作者： Yu Wu Daiqiang Huang Huanyu Zhang Anita Guarino Rosalba Fittipaldi Chao Ma Wenjie Hu Chang Niu Zhen Wang Weichao Yu Yuriy Yerin Antonio Vecchione Yang Liu Mario Cuoco Hangwen Guo Jian Shen State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 People's Republic of China Department of Physics Fudan University Shanghai 200433 People's Republic of China Shanghai Aerospace Control Technology Institute Shanghai 201109 People's Republic of China International Center for Quantum Materials Peking University Beijing 100871 People's Republic of China CNR-SPIN c/o Universitá di Salerno I-84084 Fisciano (SA) Italy College of Materials Science and Engineering Hunan University Changsha 410082 People's Republic of China Department of Physics University of Science and Technology of China Hefei Anhui 230026 Peoples Republic of China CNR-SPIN via del Fosso del Cavaliere 100 00133 Roma Italy Hefei National Laboratory Hefei 230088 People's Republic of China Zhangjiang Fudan International Innovation Center Fudan University Shanghai 201210 People's Republic of China Shanghai Research Center for Quantum Sciences Shanghai 201315 People's Republic of China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093 People's Republic of China

The relation between superconductivity and time-reversal symmetry is one of the most fascinating problems in condensed-matter physics. Here we report an anomalous transport behavior in superconducting Josephson junctions induced by surface disorder. We fabricate vertical Josephson junctions using metallic superconductor (Al) and ion-bombarded Sr2RuO4. Below the superconducting transition temperature, we observe persistent magnetoresistive hysteresis behavior dependent on the disorder deposition time. Field- and temperature-dependent measurements suggest that the observed effects arise from disorder-induced anomalous flux in Sr2RuO4 which can be sensitively detected by superconducting Al. To account for the observed findings, we consider different physical scenarios such as interband surface pairing reconstruction, magnetic surface states, and vortex phases.

关键词： Hysteresis

A robust and generalized framework for adversarial graph embedding

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arXiv 2021年

作者： Li, Jianxin Fu, Xingcheng Peng, Hao Wang, Senzhang Zhu, Shijie Sun, Qingyun Yu, Philip S. He, Lifang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China State Key Laboratory of Software Development Environment Beihang University Beijing100083 China School of Computer Science and Engineering Central South University Changsha410083 China Department of Computer Science University of Illinois at Chicago ChicagoIL60607 United States Department of Computer Science and Engineering Lehigh University BethlehemPA18015 United States

Graph embedding is essential for graph mining tasks. With the prevalence of graph data in real-world applications, many methods have been proposed in recent years to learn high quality graph embedding vectors various types of graphs. However, most existing methods usually randomly select the negative samples from the original graph to enhance the training data without considering the noise. In addition, most of these methods only focus on the explicit graph structures and cannot fully capture complex semantics of edges such as various relationships or asymmetry. In order to address these issues, we propose a robust and generalized framework for adversarial graph embedding based on generative adversarial networks. Inspired by generative adversarial network, we propose a robust and generalized framework for adversarial graph embedding, named AGE. AGE generates the fake neighbor nodes as the enhanced negative samples from the implicit distribution, and enables the discriminator and generator to jointly learn each node's robust and generalized representation. Based on this framework, we propose three models to handle three types of graph data and derive the corresponding optimization algorithms, i.e., UG-AGE and DG-AGE for undirected and directed homogeneous graphs, respectively, and HIN-AGE for heterogeneous information networks. Extensive experiments show that our methods consistently and significantly outperform existing state-of-the-art methods across multiple graph mining tasks, including link prediction, node classification, and graph reconstruction. Copyright © 2021, The Authors. All rights reserved.

关键词： Directed graphs

Measurement of the cosmic ray proton spectrum around the knee region with LHAASO 38

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Measurement of the cosmic ray proton spectrum around the kne...

38th International Cosmic Ray Conference, ICRC 2023

作者： Zhiyong, You Shoushan, Zhang Liqiao, Yin Lingling, Ma Zhen, Cao Yudong, Wang Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, L.X. Bai, Y.X. Bai, L.X. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, H. Cai, J.T. Cao, Zhe Chang, J. Chang, J.F. Chen, B.M. Chen, E.S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, X.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, S.W. Cui, X.H. Cui, Y.D. D’Ettorre Piazzoli, B. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.J. Duan, K.K. Fan, J.H. Fan, Y.Z. Fan, Z.X. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, Y.L. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Ge, M.M. Geng, L.S. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, J.G. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.C. He, S.L. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, C. Hu, H.B. Hu, S. Hu, S.C. Hu, X.J. Huang, D.H. Huang, Q.L. Huang, W.H. Huang, X.T. Huang, X.Y. Huang, Z.C. Ji, F. Ji, X.L. Jia, H.Y. Jiang, K. Jiang, Z.J. Jin, C. Ke, T. Kuleshov, D. Levochkin, K. Li, B.B. Li, Cheng Li, Cong Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, K. Li, W.L. Li, X.R. Li, Xin Li, Xin Li, Y. Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.S. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Liu, Z.X. Long, W.J. Lu, R. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Masood, A. Min, Z. Mitthumsiri, W. Montaruli, T. Nan, Y.C. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Rulev, V. Sáiz, A. Shao, L. Shchegolev, O. Sheng, X.D. Shi, J.Y. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. The Institute of High Energy Physics The Chinese Academy of Sciences YuQuan Road.19B shijingshan district Beijing China University of Chinese Academy of Sciences Department YuQuan Road.19A shijingshan district Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Key Laboratory of Particle Astrophyics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China College of Physics Sichuan University Sichuan Chengdu610065 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China School of Physics and Technology Wuhan University Hubei Wuhan430072 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai519000 China Dipartimento di Fisica dell’Università di Napoli ‘Federico II" Complesso Universitario di Monte Sant’Angelo via Cinthia Napoli80126 Italy School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Departement de Physique Nucleair

One of the main scientific aims of LHAASO is to measure the energy spectra of cosmic rays for individual mass compositions. LHAASO is made up of three detector arrays, which are WFCTA, KM2A, and WCDA. The three detector arrays can achieve hybrid observation, so several extensive air shower observables that are sensitive to mass compositions can be measured simultaneously. ROOT-TMVA package is used to combine these component-sensitive parameters for selecting proton events. The selected proton events have a purity of over 90%. In this paper, we have selected simulated events with shower cores located in the KM2A array to investigate the feasibility of the analysis method for studying the proton energy spectrum. We have also studied the associated systematic uncertainties, including those introduced by the composition models, proton selection, energy reconstruction method, and hadronic interaction models. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmic rays