Efficient mapping for Anderson impurity problems with matrix product states

TL;DR

This paper introduces a new matrix product state algorithm for Anderson impurity problems that reduces entanglement and extends to finite temperatures, improving computational efficiency in quantum many-body simulations.

Contribution

A novel chain mapping method that lowers entanglement in matrix product state simulations of Anderson impurity problems, applicable to finite temperature and dynamic scenarios.

Findings

Significantly lower entanglement compared to previous methods

Efficient simulation of Anderson impurity models at finite temperatures

Applicable to dynamical mean field theory and quantum transport

Abstract

We propose an efficient algorithm to numerically solve Anderson impurity problems using matrix product states. By introducing a modified chain mapping we obtain significantly lower entanglement, as compared to all previous attempts, while keeping the short-range nature of the couplings. Our approach naturally extends to finite temperatures, with applications to dynamical mean field theory, non-equilibrium dynamics and quantum transport.