Assessing the performance of the Random Phase Approximation for exchange and superexchange coupling constants in magnetic crystalline solids

TL;DR

This study evaluates the Random Phase Approximation's ability to accurately predict exchange interactions in various magnetic solids, comparing its performance to simpler methods like DFT+U.

Contribution

The paper systematically assesses RPA's effectiveness in capturing superexchange and direct exchange in magnetic solids, highlighting its accuracy and computational considerations.

Findings

RPA accurately corrects large errors of Hartree-Fock in magnetic interactions.

DFT+U often achieves similar accuracy with less computational effort.

RPA's performance is consistent across diverse magnetic materials.

Abstract

The Random Phase Approximation (RPA) for total energies has previously been shown to provide a qualitatively correct description of static correlation in molecular systems, where density functional theory (DFT) with local functionals are bound to fail. This immediately poses the question of whether the RPA is also able to capture the correct physics of strongly correlated solids such as Mott insulators. Due to strong electron localization, magnetic interactions in such systems are dominated by superexchange, which in the simplest picture can be regarded as the analogue of static correlation for molecules. In the present work we investigate the performance of the RPA for evaluating both superexchange and direct exchange interactions in the magnetic solids NiO, MnO, Na3Cu2SbO6, Sr2CuO3, Sr2CuTeO6, and a monolayer of CrI3, which are chosen to represent a broad variety of magnetic interactions. It is found that the RPA can accurately correct the large errors introduced by Hartree-Fock - independent of the input orbitals used for the perturbative expansion. However, in most cases, accuracies similar to RPA can be obtained with DFT+U, which is significantly simpler from a computational point of view.