Woerner, Stefan - Search Results - CERN Document Server

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Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC / Wu, Sau Lan (Wisconsin U., Madison) ; Sun, Shaojun (Wisconsin U., Madison) ; Guan, Wen (Wisconsin U., Madison) ; Zhou, Chen (Wisconsin U., Madison) ; Chan, Jay (Wisconsin U., Madison) ; Cheng, Chi Lung (Wisconsin U., Madison) ; Pham, Tuan (Wisconsin U., Madison) ; Qian, Yan (Wisconsin U., Madison) ; Wang, Alex Zeng (Wisconsin U., Madison) ; Zhang, Rui (Wisconsin U., Madison) et al.
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In this study, we employ a support vector machine with a quantum kernel estimator (QSVM-Kernel method) to a recent LHC flagship physics analysis: $t\bar{t}H$ (Higgs boson production in association with a top quark pair). [...]
arXiv:2104.05059; FERMILAB-PUB-21-552-DI-QIS.- 2021-09-08 - 9 p. - Published in : Phys. Rev. Res. 3 (2021) 033221 Fulltext: PDF; Fulltext from Publisher: PDF; Fulltext from publisher: PDF; External link: Fermilab Library Server

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1	Woerner, Stephanie
2	Woerner, Stephanie L

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