Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory
Abstract
In this work, 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 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 the 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.
- Publication Date:
- Research Org.:
- California Institute of Technology (CalTech), Pasadena, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1803262
- Grant/Contract Number:
- SC0018140
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Chemical Theory and Computation
- Additional Journal Information:
- Journal Volume: 16; Journal Issue: 1; Journal ID: ISSN 1549-9618
- Publisher:
- American Chemical Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; Chemistry; Physics; Impurities; Oxides; Nitrides; Hamiltonians; Electrical conductivity
Citation Formats
Zhu, Tianyu, Cui, Zhi-Hao, and Chan, Garnet Kin-Lic. Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory. United States: N. p., 2019.
Web. doi:10.1021/acs.jctc.9b00934.
Zhu, Tianyu, Cui, Zhi-Hao, & Chan, Garnet Kin-Lic. Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory. United States. https://doi.org/10.1021/acs.jctc.9b00934
Zhu, Tianyu, Cui, Zhi-Hao, and Chan, Garnet Kin-Lic. Mon .
"Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory". United States. https://doi.org/10.1021/acs.jctc.9b00934. https://www.osti.gov/servlets/purl/1803262.
@article{osti_1803262,
title = {Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory},
author = {Zhu, Tianyu and Cui, Zhi-Hao and Chan, Garnet Kin-Lic},
abstractNote = {In this work, 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 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 the 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.},
doi = {10.1021/acs.jctc.9b00934},
journal = {Journal of Chemical Theory and Computation},
number = 1,
volume = 16,
place = {United States},
year = {Mon Dec 09 00:00:00 EST 2019},
month = {Mon Dec 09 00:00:00 EST 2019}
}
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