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Jet tagging algorithm of graph network with Haar pooling message passing

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成果类型:
期刊论文
作者:
Fei Ma;Feiyi Liu;Wei Li
作者机构:
[Fei Ma] Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, WuHan, 430079, China
Institute for Physics, Eötvös Loránd University, 1/A Pázmány P. Sétány, H-1117, Budapest, Hungary
Max-Planck-Institute for Mathematics in the Sciences, 04103 Leipzig, Germany
[Feiyi Liu] Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, WuHan, 430079, China<&wdkj&>Institute for Physics, Eötvös Loránd University, 1/A Pázmány P. Sétány, H-1117, Budapest, Hungary
[Wei Li] Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, WuHan, 430079, China<&wdkj&>Max-Planck-Institute for Mathematics in the Sciences, 04103 Leipzig, Germany
语种:
英文
期刊:
PHYSICAL REVIEW D
ISSN:
2470-0010
年:
2023
卷:
108
期:
7
页码:
072007
基金类别:
Fundamental Research Funds for the Central Universities#&#&#CCNU19QN029 National Natural Science Foundation of China#&#&#11505071#&#&#61702207#&#&#61873104 Higher Education Discipline Innovation Project#&#&#BP0820038
机构署名:
本校为第一机构
院系归属:
物理科学与技术学院
摘要:
Recently, methods of graph neural networks (GNNs) have been applied to solving the problems in high-energy physics (HEP) and have shown its great potential for quark-gluon tagging with graph representation of jet events. In this paper, we introduce an approach of GNNs combined with a Haar pooling operation to analyze the events, called Haar pooling message passing neural network (HMPNet). In HMPNet, Haar pooling not only extracts the features of graph, but embeds additional information obtained by clustering of k means of different particle fea...

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