Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational pa...

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Detalles Bibliográficos
Autores principales: Wu, Sau Lan, Chan, Jay, Cheng, Alkaid, Guan, Wen, Sun, Shaojun, Wang, Alex, Zhang, Rui, Zhou, Chen, Livny, Miron, Di Meglio, Alberto, Li, Andy, Lykken, Joseph, Spentzouris, Panagiotis, Yen-Chi Chen, Samuel, Yoo, Shinjae, Wei, Tzu-Chieh, Lougovski, Pavel, Padhi, Sanjay, Severini, Simone, Walker, Dewayne
Lenguaje:eng
Publicado: 2022
Materias:
Detectors and Experimental Techniques
Quantum Technology
Acceso en línea:https://dx.doi.org/10.22323/1.398.0842
http://cds.cern.ch/record/2827277

Internet

https://dx.doi.org/10.22323/1.398.0842
http://cds.cern.ch/record/2827277

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