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Application of Quantum Machine Learning using the Quantum Variational Classifier Method to High Energy Physics Analysis at the LHC on IBM Quantum Computer Simulator and Hardware with 10 qubits
One of the major objectives of the experimental programs at the Large Hadron Collider (LHC) is the discovery of new physics. This requires the identification of rare signals in immense backgrounds. Using machine learning algorithms greatly enhances our ability to achieve this objective. With the pro...
Autores principales: | Wu, Sau Lan, Chan, Jay, Guan, Wen, Sun, Shaojun, Wang, Alex, Zhou, Chen, Livny, Miron, Carminati, Federico, Di Meglio, Alberto, Li, Andy C.Y., Lykken, Joseph, Spentzouris, Panagiotis, Chen, Samuel Yen-Chi, Yoo, Shinjae, Wei, Tzu-Chieh |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1361-6471/ac1391 http://cds.cern.ch/record/2748292 |
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