Application of quantum machine learning using the quantum kernel algorithm on high energy physics analysis at the LHC
We studied a support vector machine with a quantum kernel estimator (SQVM-Kernel) for classification of proton-proton final states, targeting the Higgs boson production associated with a pair of top quarks. Using a dataset of 50000 events, we demonstrated the evquivalent performance of the quantum algorithm compared to the classical counterparts.