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Efficient Semi-numerical Implementation of Global and Local Hybrid Functionals for Time-Dependent Density Functional
Toni M Maier1, Hilke Bahmann1, Martin Kaupp1
1Institut für Chemie Theoretische Chemie/Quantenchemie, Technische Universität Berlin , Sekr. C7 Straße des 17. Juni 135, D-10623, Berlin, Germany.
Local hybrid functionals offer enhanced flexibility for electronic excitations. A new semi-numerical method makes time-dependent density functional theory (TDDFT) calculations with local hybrids efficient, even for large systems.
Area of Science:
- Computational Chemistry
- Quantum Chemistry
- Theoretical Chemistry
Background:
- Local hybrid functionals provide greater flexibility than global hybrids.
- This flexibility is anticipated to benefit calculations of electronic excitations using time-dependent density functional theory (TDDFT).
Purpose of the Study:
- To report the first linear-response TDDFT implementation of local hybrid functionals using a semi-numerical integration technique.
- To evaluate the efficiency and accuracy of this new implementation.
Main Methods:
- A semi-numerical integration technique was employed for the linear-response TDDFT implementation of local hybrid functionals.
- The performance was assessed by comparing timings and accuracy against analytical methods for time-dependent Hartree-Fock (TDHF) and the TPSSh global hybrid.
- The Resolution of Identity (RI) approximation was used for the Coulomb part of the kernel.
Main Results:
- The semi-numerical implementation is faster than existing analytical methods for global hybrid functionals in the TURBOMOLE code, even for small systems.
- Timings for global and local hybrids are comparable with the semi-numerical approach.
- The new method facilitates TDDFT calculations with local hybrid functionals for large systems.
Conclusions:
- The development of a semi-numerical linear-response TDDFT implementation of local hybrid functionals opens new possibilities for computational chemistry.
- This approach enables efficient calculations for larger systems, paving the way for evaluating more sophisticated local hybrid functional parametrizations.
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