Pairing correlations in the cuprates: a numerical study of the three-band Hubbard model

ORAL

Abstract

We study the three-band Hubbard model for the copper oxide plane of the high-temperature superconducting cuprates using exact diagonalization, determinant quantum Monte Carlo, and dynamical cluster approximation (DCA) with an emphasis on pairing correlations. Using these methods, we provide a comprehensive view of pairing in the model. Specifically, we compute the pair-field susceptibility for these methods and study its dependence on temperature, doping, interaction strength, and charge-transfer gap. Using DCA, we also solve the Bethe-Salpeter equation for two-particle Green’s function to identify the dominant pairing correlations and its orbital composition, and to determine the transition temperature to the superconducting state.

*This work was supported by the Scientific Discovery through Advanced Computing (SciDAC) program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences, Division of Materials Sciences and Engineering.

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Presenters

  • Peizhi Mai

    • Oak Ridge National Laboratory
    • Oak Ridge National Lab

Authors

  • Peizhi Mai

    • Oak Ridge National Laboratory
    • Oak Ridge National Lab

  • 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

  • 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