Demonstrating scalable randomized benchmarking of universal gate sets

ORAL

Abstract

Randomized benchmarking (RB) protocols are the most widely used methods for assessing the performance of quantum gates. However, the existing RB methods either do not scale to many qubits or cannot benchmark a universal gate set. Here we introduce and demonstrate a technique for scalable RB of certain universal and continuously parameterized gate sets, using a class of circuits called randomized mirror circuits. Our technique can be applied to a gate set containing an entangling Clifford gate and the set of arbitrary single-qubit gates, as well as gate sets containing controlled rotations about the Pauli axes. We use our technique to benchmark universal gate sets on four qubits of the Advanced Quantum Testbed, including a gate set containing a controlled S gate and its inverse, and we investigate how the observed error rate is impacted by the inclusion of non-Clifford gates. Finally, we demonstrate that our technique scales to many qubits with experiments on a 27-qubit IBM Q processor.

*This work was supported in part by the LDRD program at SNL and by the US DOE SC/ASCR's Quantum Testbeds for Science Program. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

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Presenters

  • Jordan Hines

    • University of California, Berkeley
    • University of California Berkeley

Authors

  • Jordan Hines

    • University of California, Berkeley
    • University of California Berkeley

  • Marie Lu

    • University of California, Berkeley

  • Ravi K Naik

    • University of California, Berkeley
    • Lawrence Berkeley National Laboratory

  • Akel Hashim

    • University of California, Berkeley

  • Jean-Loup Ville

    • University of California, Berkeley

  • Brad Mitchell

    • Lawrence Berkeley National Laboratory

  • John Mark Kreikebaum

    • Lawrence Berkeley National Laboratory

  • David I Santiago

    • Lawrence Berkeley National Laboratory
    • Computational Research Division, Lawrence Berkeley National Lab

  • Erik Nielsen

    • Sandia National Laboratories

  • Kevin C Young

    • Sandia National Laboratories

  • Robin J Blume-Kohout

    • Sandia National Laboratories

  • Irfan Siddiqi

    • University of California, Berkeley
    • Applied Mathematics and Computational Research and Materials Sciences Divisions, LBNL
    • Lawrence Berkeley National Laboratory
    • Applied Mathematics, Computational Research and Materials Sciences Divisions, Lawrence Berkeley National Lab

  • Birgitta Whaley

    • University of California, Berkeley

  • Timothy J Proctor

    • Sandia National Laboratories