Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory

TL;DR

This paper introduces an efficient ab initio dynamical mean-field theory (DMFT) method for accurate quantum simulations of solids, capable of handling large impurity problems with hundreds of orbitals.

Contribution

The paper develops a scalable ab initio DMFT implementation using realistic basis sets and advanced impurity solvers, reducing double counting and enabling large-scale periodic system simulations.

Findings

Accurate spectral functions for solids matching experimental data.

Ability to handle impurity problems with over 100 orbitals.

Demonstrated application to BN monolayer, silicon, and nickel oxide.

Abstract

We present an efficient ab initio dynamical mean-field theory (DMFT) implementation for quantitative simulations in solids. Our DMFT scheme employs ab initio Hamiltonians defined for impurities comprising the full unit cell or a supercell of atoms and for realistic quantum chemical basis sets. We avoid double counting errors by using Hartree-Fock as the low-level theory. Intrinsic and projected atomic orbitals (IAO+PAO) are chosen as the local embedding basis, facilitating numerical bath truncation. Using an efficient integral transformation and coupled-cluster Green's function (CCGF) impurity solvers, we are able to handle embedded impurity problems with several hundred orbitals. We apply our ab initio DMFT approach to study a hexagonal boron nitride monolayer, crystalline silicon, and nickel oxide in the antiferromagnetic phase, with up to 104 and 78 impurity orbitals in spin-restricted and unrestricted cluster DMFT calculations and over 100 bath orbitals. We show that our scheme produces accurate spectral functions compared to both benchmark periodic coupled-cluster computations and experimental spectra.