APS Logo

Leveraging Randomized Compiling for the QITE Algorithm

ORAL

Abstract

Recent progress on quantum hardware has enabled the successful implementation of quantum algorithms to simulate small molecules or textbook condensed matter models on a limited number of qubits. The results of quantum algorithms executed on such NISQ hardware are, however, limited by the remaining noise, mainly on the multi-qubit gates. Randomized compiling has recently been shown to mitigate the coherent part of the noise to, easier to handle, stochastic noise. In this work, we implement a new noise-mitigation technique, taking advantage of the noise tailoring property of randomized compiling, and then compensating for the stochastic noise. We apply this method to the quantum imaginary time evolution (QITE) algorithm which has attracted a lot of attention recently and is very sensitive to the measurement of expectation values, making it a good benchmark for our scheme. Our method is simple to implement and does not require any additional hardware.

–

Presenters

  • Jean-Loup Ville

    University of California, Berkeley, University of California - Berkeley

Authors

  • Jean-Loup Ville

    University of California, Berkeley, University of California - Berkeley

  • Alexis Morvan

    University of California, Berkeley, Lawrence Berkeley National Laboratory, Laboratoire de Physique des Solides, CNRS - Université Paris Saclay

  • Akel Hashim

    Univ of California – Berkeley, University of California, Berkeley, Quantum Nanoelectronics Lab, UC Berkeley, University of California - Berkeley

  • Ravi K. Naik

    University of California, Berkeley, Univ of California – Berkeley, Physics, University of California, Berkeley, University of California Berkeley, Univ of California - Berkeley, Quantum Nanoelectronics Laboratory, Dept. of Physics, University of California, Berkeley, University of California - Berkeley

  • Brad Mitchell

    University of California, Berkeley, Univ of California – Berkeley, University of California - Berkeley

  • John Mark Kreikebaum

    Lawrence Berkeley National Laboratory, University of California, Berkeley, Univ of California – Berkeley, Physics, University of California, Berkeley

  • Kevin O'Brien

    Massachusetts Institute of Technology MIT, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Univ of California – Berkeley, Massachusetts Institute of Technology

  • Marc Davis

    Lawrence Berkeley National Laboratory

  • Ethan Smith

    University of California Berkeley, Lawrence Berkeley National Laboratory

  • Ed Younis

    Lawrence Berkeley National Lab, Lawrence Berkeley National Laboratory

  • Costin Iancu

    Lawrence Berkeley National Lab, Lawrence Berkeley National Laboratory

  • Ian Hincks

    Quantum Benchmark, Inc.

  • Joel Wallman

    University of Waterloo, Quantum Benchmark, Inc.

  • Joseph V Emerson

    Quantum Benchmark, Inc.

  • David Ivan Santiago

    Lawrence Berkeley National Laboratory, University of California, Berkeley, Lawrence Berkely National Laboratory, Quantum Nanoelectronics Laboratory, Dept. of Physics, University of California, Berkeley

  • Irfan Siddiqi

    Lawrence Berkeley National Laboratory, University of California, Berkeley, Univ of California - Berkeley, Univ of California – Berkeley, Quantum Nanoelectronics Lab, UC Berkeley, Physics, University of California, Berkeley, Quantum Nanoelectronics Laboratory, Dept. of Physics, University of California, Berkeley