Zc(3900) observation at BESIII with QSVM method

被引：0
|
作者：
Ding, Biao [1 ,2 ]
Meng, Zhaoxia [1 ]
Zou, Jiaheng [2 ]
Li, Teng [3 ]
Lin, Tao [2 ]
机构：
[1] Univ Jinan, Guangzhou, Peoples R China
[2] Inst High Energy Phys, Beijing, Peoples R China
[3] Shandong Univ, Jinan, Peoples R China
来源：
26TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS, CHEP 2023 | 2024年 / 295卷
关键词：
D O I：
10.1051/epjconf/202429512008
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In recent years, quantum computing shows significant potentials in many areas. In this proceeding, we revisit the observation of the Zc(3900) resonance with quantum machine learning techniques, specifically quantum support vector machine (QSVM). Meanwhile, the outcomes are compared with classical support vector machine (SVM) method. With the IBM Qiskit toolkit, the QSVM method achieves a competitive signal and background classification accuracy compared to classical methods. This study emphasizes the potential of quantum machine learning in high-energy physics research, and it reveals the feasibility of applying quantum computing in future physics data analysis.
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页数：4
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