Abstract
The quantitative prediction of electronic properties in correlated materials requires simulations without empirical truncations and parameters. We present a method to achieve this goal through a new ab initio formulation of dynamical mean-field theory (DMFT). Instead of using small impurities defined in a low-energy subspace, which require complicated downfolded interactions which are often approximated, we describe a full cell approach, where the impurities comprise all atoms in a unit cell or supercell of the crystal. Our formulation results in large impurity problems, which we treat here with efficient quantum chemistry impurity solvers that work on the real-frequency axis, combined with a one-shot treatment of long-range interactions. We apply our full cell approach to bulk Si, two antiferromagnetic correlated insulators NiO and , and the paramagnetic correlated metal , with impurities containing up to ten atoms and 124 orbitals. We find that spectral properties, magnetic moments, and two-particle spin correlation functions are obtained in good agreement with experiment. In addition, in the metal oxide insulators, the balanced treatment of correlations involving all orbitals in the cell leads to new insights into the orbital character around the insulating gap.
- Received 7 March 2020
- Revised 13 November 2020
- Accepted 4 January 2021
DOI:https://doi.org/10.1103/PhysRevX.11.021006
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Popular Summary
The development of certain materials with unusual electronic or magnetic properties, such as high-temperature superconductors, requires taking into account how the electrons interact with each other. But predicting the properties of such correlated electron materials from first principles remains a significant challenge. To tackle this, “quantum embedding methods” have been developed to make the problem tractable, but their predictive power is often hindered by a variety of different approximations. Here, we present a formulation of quantum embedding that avoids some of these approximations, to obtain quantitative accuracy in correlated electron materials simulations.
Quantum embedding methods map an infinite bulk solid to a finite impurity system, which in turn can be explicitly studied by highly accurate many-body theories. In previous strategies, a small number of strongly correlated orbitals first must be identified to constitute the impurity problem.
In our approach, based on dynamical mean-field theory, we incorporate all orbitals in a material supercell into the dynamical mean-field theory impurity. As a consequence, we can remove the ambiguities associated with choosing the orbitals and provide a more faithful representation of the intermediate-range correlations of the system. By deploying techniques from quantum chemistry and many-body perturbation theory, we show that our method approaches quantitative accuracy in calculating the spectral properties of a wide range of semiconducting, insulating, and metallic materials.
More broadly, our framework helps unify modern advances in quantum chemistry and modeling of correlated electron materials, opening up further cross-fertilization of these disciplines.
