Solving a Higgs optimization problem with quantum annealing for machine learning

Alex Mott, Joshua Job, Jean-Roch Vlimant, Daniel Lidar and Maria Spiropulu ()
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Alex Mott: California Institute of Technology
Joshua Job: University of Southern California
Jean-Roch Vlimant: California Institute of Technology
Daniel Lidar: Center for Quantum Information Science and Technology, University of Southern California
Maria Spiropulu: California Institute of Technology

Nature, 2017, vol. 550, issue 7676, 375-379

Abstract: A machine learning algorithm implemented on a quantum annealer—a D-Wave machine with 1,098 superconducting qubits—is used to identify Higgs-boson decays from background standard-model processes.

Date: 2017
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DOI: 10.1038/nature24047

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