Multiconfiguration Pair-Density Functional Theory for Strongly Correlated Systems
ORAL · Invited
Abstract
An overview of recent developments in multiconfiguration pair-density functional theory (MC-PDFT) will be presented, with special emphasis on linearized PDFT (L-PDFT).[1]
The method involves the construction of an effective L-PDFT Hamiltonian operator, achieved by expanding the MC-PDFT energy expression to first-order in a Taylor series of the wave function density. This approach allows for the accurate prediction of potential energy surface topologies near conical intersections and locally avoided crossings, even in challenging cases like phenol, methylamine, and the spiro cation.
Additionally, we will introduce quantum embedding and localization methods tailored to characterize systems ranging from extended, strongly correlated molecules to periodic systems. We will present the integration of quantum embedding with MC-PDFT, utilizing densities derived from periodic density matrix embedding theory.[2] Our discussion will feature examples of calculations related to local excitations within both solid-state materials and molecules.
[1] Hennefarth, M. Hermes, D. Truhlar, and L. Gagliardi, Linearized Pair-Density Functional Theory, J. Chem. Theory Comput., 2023, 19, 3172–3183 DOI: 10.1021/acs.jctc.3c00207
[2] A. Mitra, M. Hermes, and L. Gagliardi, Density Matrix Embedding Using Multiconfiguration Pair-Density Functional Theory, J. Chem. Theory Comput., 2023, 19, 3498–3508 DOI: https://doi.org/10.1021/acs.jctc.3c00247
* This work was supported in part by the National Science Foundation under Grant CHE-2054723. We also acknowledge the University of Chicago’s Research Computing Center for their support of this work. This material is also based upon work supported by the U.S. Department of Energy Office of Science National Quantum Information Science Research Centers.
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Publication: [1] Hennefarth, M. Hermes, D. Truhlar, and L. Gagliardi, Linearized Pair-Density Functional Theory, J. Chem. Theory Comput., 2023, 19, 3172–3183 DOI: 10.1021/acs.jctc.3c00207
[2] A. Mitra, M. Hermes, and L. Gagliardi, Density Matrix Embedding Using Multiconfiguration Pair-Density Functional Theory, J. Chem. Theory Comput., 2023, 19, 3498–3508 DOI: https://doi.org/10.1021/acs.jctc.3c00247
Presenters
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Laura Gagliardi
University of Chicago, University of Minnesota
Authors
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Laura Gagliardi
University of Chicago, University of Minnesota
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Donald G Truhlar
University of Minnesota
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Matthew Hermes
University of Chicago
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Abhishek Mitra
University of Chicago
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Matthew Hennefarth
University of Chicago
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Shreya Verma
University of Chicago