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Stretching Bonds without Breaking Symmetries in Density Functional Theory
Yuming Shi1, Yi Shi2, Adam Wasserman1,2
1Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana 47907, United States.
This study introduces a new computational method using fragment spin densities to resolve the "symmetry dilemma" in Kohn-Sham density functional theory (KS-DFT). The approach improves energy calculations for molecules without breaking charge or spin symmetries.
Area of Science:
- Computational Chemistry
- Quantum Mechanics
- Electronic Structure Theory
Background:
- Kohn-Sham density functional theory (KS-DFT) offers a balance of accuracy and efficiency for electronic structure calculations.
- A persistent challenge in KS-DFT is the "symmetry dilemma," where achieving chemically accurate energies requires breaking fundamental symmetries.
- Standard density functional approximations often necessitate artificial symmetry breaking for accurate results.
Purpose of the Study:
- To present an embedding framework that addresses the symmetry dilemma in KS-DFT.
- To develop a method that improves the accuracy of energy calculations without compromising charge or spin symmetries.
- To explore a new computational approach using fragment spin densities as primary variables.
Main Methods:
- Developed an embedding framework utilizing fragment spin densities instead of total molecular densities.
- Constructed a novel functional approximation, termed the "overlap approximation," based on the spatial overlap of fragment densities.
- Applied the method to assess binding energies of molecules, including covalently bonded and strongly correlated systems.
Main Results:
- The proposed embedding framework partially resolves the symmetry dilemma inherent in KS-DFT.
- The "overlap approximation" significantly improves the accuracy of semilocal KS-DFT binding energies.
- The method successfully avoids artificial breaking of charge and spin symmetries in calculations.
Conclusions:
- The fragment spin density embedding approach offers a promising solution to the KS-DFT symmetry dilemma.
- This physically motivated "overlap approximation" enhances computational accuracy for molecular systems.
- The framework demonstrates applicability to diverse chemical systems, including challenging strongly correlated ones.
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