Precise evaluation of thermal response functions by optimized density matrix renormalization group schemes

TL;DR

This paper introduces and analyzes optimized tDMRG schemes for accurately computing finite-temperature response functions in strongly correlated quantum systems, significantly extending the accessible simulation times.

Contribution

It presents a new class of near-optimal tDMRG schemes that improve computational efficiency and extend simulation times for finite-temperature response functions.

Findings

New optimized tDMRG schemes increase maximum simulation times by a factor of two.

The schemes are applicable to various phases of the XXZ Heisenberg chain.

The approach simplifies the relation between matrix product states and operators.

Abstract

This paper provides a study and discussion of earlier as well as novel more efficient schemes for the precise evaluation of finite-temperature response functions of strongly correlated quantum systems in the framework of the time-dependent density matrix renormalization group (tDMRG). The computational costs and bond dimensions as functions of time and temperature are examined for the example of the spin-1/2 XXZ Heisenberg chain in the critical XY phase and the gapped N\'eel phase. The matrix product state purifications occurring in the algorithms are in one-to-one relation with corresponding matrix product operators. This notational simplification elucidates implications of quasi-locality on the computational costs. Based on the observation that there is considerable freedom in designing efficient tDMRG schemes for the calculation of dynamical correlators at finite temperatures, a new class of optimizable schemes, as recently suggested in arXiv:1212.3570, is explained and analyzed numerically. A specific novel near-optimal scheme that requires no additional optimization reaches maximum times that are typically increased by a factor of two, when compared against earlier approaches. These increased reachable times make many more physical applications accessible. For each of the described tDMRG schemes, one can devise a corresponding transfer matrix renormalization group (TMRG) variant.