Quantum-classical simulation of two-site dynamical mean-field theory on noisy quantum hardware

ORAL

Abstract

We report on a quantum-classical simulation of a two-site dynamical mean-field theory (DMFT) calculation. We use IBM's superconducting qubit chip to compute the zero-temperature impurity Green's function in the time domain and a classical computer to fit the measured Green's function. We find that Trotter errors and noise from the quantum chip lead to inaccurate updates to impurity parameters, preventing the DMFT algorithm from converging to the correct solution. To mitigate this issue, we determine the update to the hybridization parameter by integrating the low-frequency peaks in the spectral function. This allows us to iterate the DMFT loop to self-consistency for a strongly Mott insulating system at half-filling.

*This work is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (ASCR) quantum algorithm teams program, proposal number ERKJ333.

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Presenters

  • Trevor Keen

    • University of Tennessee, Knoxville

Authors

  • Trevor Keen

    • University of Tennessee, Knoxville

  • Thomas Maier

    • Computational Sciences and Engineering Division and Center for Nanophase Materials Sciences, Oak Ridge National Laboratory
    • Oak Ridge National Laboratory
    • Oak Ridge National Lab
    • Center for Nanophase Materials Sciences,Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6164, USA and Computational Sciences and Engineering Division, Oak Ridge Nat
    • Computational Sciences and Engineering Division, Oak Ridge National Laboratory

  • Steven Johnston

    • Department of Physics and Astronomy, University of Tennessee knoxville
    • University of Tennessee, Knoxville
    • University of Tennessee in Knoxville
    • Department of Physics and Astronomy, The University of Tennessee, Knoxville, Tennessee 37996, USA and Joint Institute of Advanced Materials at The University of Tennessee, Kn

  • Pavel Lougovski

    • Computational Sciences and Engineering Division, Oak Ridge National Laboratory
    • Oak Ridge National Lab