Imaginary-time matrix product state impurity solver for dynamical mean-field theory

TL;DR

This paper introduces a new impurity solver for dynamical mean-field theory using imaginary-time matrix product states, enabling larger system studies with less entanglement and improved efficiency.

Contribution

The paper develops a novel imaginary-time matrix product state impurity solver that improves upon existing methods in efficiency and system size capability.

Findings

Successfully applied to a three-band model in single and two-site DMFT.

Reduces bath size and entanglement compared to real-frequency methods.

Discusses technical advantages and potential applications of the method.

Abstract

We present a new impurity solver for dynamical mean-field theory based on imaginary-time evolution of matrix product states. This converges the self-consistency loop on the imaginary-frequency axis and obtains real-frequency information in a final real-time evolution. Relative to computations on the real-frequency axis, required bath sizes are much smaller and less entanglement is generated, so much larger systems can be studied. The power of the method is demonstrated by solutions of a three band model in the single and two-site dynamical mean-field approximation. Technical issues are discussed, including details of the method, efficiency as compared to other matrix product state based impurity solvers, bath construction and its relation to real-frequency computations and the analytic continuation problem of quantum Monte Carlo, the choice of basis in dynamical cluster approximation, and perspectives for off-diagonal hybridization functions.