Correlation Functions From Tensor Network Influence Functionals: The Case of the Spin-Boson Model
Abstract
We investigate the application of matrix product state (MPS) representations of the influence functionals (IF) for the calculation of real-time equilibrium correlation functions in open quantum systems. Focusing specifically on the unbiased spin-boson model, we explore the use of IF-MPSs for complex time propagation, as well as IF-MPSs for constructing correlation functions in the steady state. We examine three different IF approaches: one based on the Kadanoff-Baym contour targeting correlation functions at all times, one based on a complex contour targeting the correlation function at a single time, and a steady state formulation which avoids imaginary or complex times, while providing access to correlation functions at all times. We show that within the IF language, the steady state formulation provides a powerful approach to evaluate equilibrium correlation functions.
Keywords
Cite
@article{arxiv.2406.15737,
title = {Correlation Functions From Tensor Network Influence Functionals: The Case of the Spin-Boson Model},
author = {Haimi Nguyen and Nathan Ng and Lachlan P. Lindoy and Gunhee Park and Andrew J. Millis and Garnet Kin-Lic Chan and David R. Reichman},
journal= {arXiv preprint arXiv:2406.15737},
year = {2025}
}