Cycle Benchmarking for Scalable Verification of Quantum Circuit Performance

COFFEE_KLATCH · Invited

Abstract

Predicting the reliability and capacity of quantum computer hardware, under some imperfectly known noise model, to perform a quantum computation, either with or without error correction, is a major challenge towards the realization of practical quantum computation. In this talk I will describe a practical framework, comprising randomized compiling and cycle benchmarking, which provides a complete and comprehensive solution to this problem. Randomized Compiling is a scalable method to dramatically reduce the most problematic errors affecting present-day quantum processors, including coherent (calibration) errors and non-Markovian errors, which tailors the error model to stochastic Pauli errors to very good approximation. Cycle benchmarking is a more efficient and practical method of randomized benchmarking which leverages randomized compiling to enable a precise and scalable method to bound the error probability of the quantum computer output for any algorithm or application based on a characterization of the actual error model affecting the hardware. These hardware-agnostic tools, which are available as a software system, imply a rigorous means of demonstrating quantum supremacy or quantum advantage in the regime beyond classically simulability.

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Authors

  • Joseph Emerson

    University of Waterloo, Univ of Waterloo

  • Alexey Feofanov

    University of Innsbruck, University of Waterloo, Korea University, Okinawa Institute of Science and Technology, University of California - Los Angeles, The University of Manchester, University of Puerto Rico at Humacao, Department of Physics & Electronics, University of Puerto Rico at Cayey, Department of Mathematics-Physics, Oak Ridge National Lab, Max Planck Institute for Chemical Physics of Solids, Department of Physics, University of Puerto Rico, Electrical Engineering Department, University of Arkansas, Department of Physics, University of Arkansas, School of Basic Sciences at IIT Mandi, H.P., India, Computational Biology, Flatiron Institute, Physics, Hong Kong Univ of Sci & Tech, University of California, Los Angeles, Max Planck Inst, Institute for Theoretical Physics, University of Cologne, Department of Physics, Simon Fraser University, Deutsches Elektronen Synchrotron (DESY), Institut fur Theoretische Physik, Univerisitat zu Berlin, Institut fur Physik, Univerisitat zu Berlin, Plymouth State University, The Graduate Center, CUNY, Nordita, KTH Royal Institute of Technology and Stockholm University, Univ of Connecticut - Storrs, Univ Stuttgart, University of Chicago, University of Texas at El Paso, University of Tulsa, California Institute of Technology, Georgia Institute of Technology, Universite Paris Diderot, Laboratoire MPQ, Universita di Trento, BEC Center, ICTP Trieste, Universita di Pisa, Inst of Physics Academia Sinica, Batelle, Cal State Univ- San Bernardino, Chemical Engineering, University of Michigan, QCD Labs, Department of Applied Physics, Aalto University, Yale University, MIT, Harvard Univ, Chemical & Environmental Engineering, University of California, Riverside, University of Frankfurt, Germany, University of Hamburg, Germany, Naval Research Laboratory, Cornell Univ, National Institute for Material Science, U.S. Naval Research Laboratory, Washington DC, Materials Engineering, University of Santa Barbara, Institute of Physics, Chinese Academy of Sciences, Univ of Texas, Arlington, MIT Lincoln Laboratory, University of Sydney, Iowa State University, Purdue University, Kansas State University, University of Maryland, John Hopkins University, Universite de Sherbrooke, Physics, Konkuk University, Perimeter Institute, University of Waterloo, D-Wave, San Jose State University, Université de Sherbrooke, Institute of Physics, EPFL - Lausanne​