Multi-orbital dynamical mean-field theory with a complex-time solver

TL;DR

This paper introduces a novel complex-time tensor-network impurity solver combined with exponential fitting for efficient multi-orbital dynamical mean-field theory, enabling high-resolution spectra with reduced computational cost.

Contribution

It develops a new complex-time approach with exponential fitting for spectral analysis in multi-orbital DMFT, improving efficiency and flexibility over existing methods.

Findings

Achieves high-resolution spectra at lower computational cost.

Balances spectral accuracy with computational efficiency.

Provides a flexible framework for strongly correlated materials.

Abstract

We present the combination of a complex-time tensor-network impurity solver with an analytic continuation scheme based on exponential fitting as an efficient framework for single and multi-orbital dynamical mean-field calculations. By performing time-evolution along a complex-time contour, the approach balances computational cost with the difficulty of spectral recovery, offering greater flexibility than methods confined to the real or imaginary axis. By complementing the complex-time evolution with an exponential fitting scheme, we faithfully extract real-time information at negligible cost. The resulting method obtains high-resolution spectra at a significantly lower computational cost than real-time evolution, offering a promising tool for ab initio studies of strongly correlated materials.