Fork Tensor Product States - Efficient Three Orbital Real Time DMFT Solver

TL;DR

This paper introduces a tensor network-based impurity solver for multi-orbital DMFT that operates directly on the real-frequency axis, providing high spectral resolution and accurate bath representation for correlated materials.

Contribution

The authors develop a novel tensor network method tailored for multi-orbital Anderson impurity models, enabling efficient and precise real-frequency spectral calculations in DMFT.

Findings

Achieves high spectral resolution across all frequencies.

Accurately models bath with around 100 sites.

Resolves multiplet structures in high-energy spectra.

Abstract

We present a tensor network especially suited for multi-orbital Anderson impurity models and as an impurity solver for multi-orbital dynamical mean-field theory (DMFT). The solver works directly on the real-frequency axis and yields very high spectral resolution at all frequencies. We use a large number $\left(\mathcal{O}(100)\right)$ of bath sites, and therefore achieve an accurate representation of the bath. The solver can treat full rotationally invariant interactions with reasonable numerical effort. We show the efficiency and accuracy of the method by a benchmark for the testbed material SrVO$_3$. There we observe multiplet structures in the high-energy spectrum which are almost impossible to resolve by other multi-orbital methods. The resulting structure of the Hubbard bands can be described as a broadened atomic spectrum with rescaled interaction parameters. Additional features emerge when $U$ is increased. The impurity solver offers a new route to the calculation of precise real-frequency spectral functions of correlated materials.