Many body Green's function using variational dynamics

ORAL

Abstract

We present a method to compute many-body real-time Green's function using adaptive variational quantum dynamics simulation. The real-time Green's function involves the time evolution of a quantum state with one additional electron w.r.t. the ground state wavefunction. Simulation of such a non-normal quantum state is achieved by expressing it as a linear combination of multiple branch states. The real-time evolution and Green's function are obtained by combining the dynamics of the individual branch states. In order to minimize the error of a convergent Fourier transform of the Green's function using finite time simulation, we use the Padé approximation of the real-time data. We apply our method to the Hubbard model at half-filling and find very good agreement with exact results. As a part of error mitigation, we develop a resolution-enhancing method that we successfully apply to noisy data.

*This work was supported by the ”Embedding QC into Many-body Frameworks for Strongly Correlated Molecular and Materials Systems” project, which is funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences (BES), the Division of Chemical Sciences, Geosciences, and Biosciences. Part of this work was supported by the Office of Science, Office of Advanced Scientific Computing Research Accelerated Research for Quantum Computing Program of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located atLawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract No.~DE-AC05-00OR22725.

–

Presenters

  • Niladri Gomes

    • Lawrence Berkeley National Laboratory

Authors

  • Niladri Gomes

    • Lawrence Berkeley National Laboratory

  • Lindsay Bassman

    • Lawrence Berkeley Lab

  • David B Williams-Young

    • Lawrence Berkeley National Laboratory

  • Wibe A de Jong

    • LBNL
    • Lawrence Berkeley National Laboratory