Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC

Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in high energy physics by offering computational speedups. In this study, we employ a support vector machine with a quantum kernel estimator (QSVM-Kernel method) to a recent LHC flags...

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Detalles Bibliográficos
Autores principales: Wu, Sau Lan, Sun, Shaojun, Guan, Wen, Zhou, Chen, Chan, Jay, Cheng, Chi Lung, Pham, Tuan, Qian, Yan, Wang, Alex Zeng, Zhang, Rui, Livny, Miron, Glick, Jennifer, Barkoutsos, Panagiotis Kl., Woerner, Stefan, Tavernelli, Ivano, Carminati, Federico, Di Meglio, Alberto, Li, Andy C.Y., Lykken, Joseph, Spentzouris, Panagiotis, Chen, Samuel Yen-Chi, Yoo, Shinjae, Wei, Tzu-Chieh
Lenguaje:eng
Publicado: 2021
Materias:
hep-ex
Particle Physics - Experiment
quant-ph
General Theoretical Physics
Acceso en línea:https://dx.doi.org/10.1103/PhysRevResearch.3.033221
http://cds.cern.ch/record/2764310

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