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Updated: Oct 10, 2025

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
Published on: May 27, 2020
Generalized Kohn-Sham equations with accurate total energy and single-particle eigenvalue spectrum
Thomas C Pitts1, Nektarios N Lathiotakis2, Nikitas Gidopoulos1
1Department of Physics, Durham University, South Road, Durham DH1 3LE, United Kingdom.
We introduce a novel hybrid method for calculating electronic structures. This approach accurately predicts ionization potentials, improving eigenvalue spectra with minimal energy cost.
Area of Science:
- Quantum Chemistry
- Computational Materials Science
- Electronic Structure Theory
Background:
- Accurate prediction of electronic structure is crucial for understanding material properties.
- Existing methods like Kohn-Sham theory face challenges with self-interaction errors.
- Improving the accuracy of single-particle eigenvalue spectra is an ongoing research goal.
Purpose of the Study:
- To develop a generalized Kohn-Sham or constrained hybrid method.
- To improve the accuracy of single-particle eigenvalue spectra.
- To minimize the increase in total energy while enhancing spectral accuracy.
Main Methods:
- A new generalized Kohn-Sham or constrained hybrid method is proposed.
- The exchange potential is an average of nonlocal Fock-exchange and self-interaction-corrected exchange potentials.
- A constrained minimization method of semi-local approximations is employed.
Main Results:
- The new method yields an accurate single-particle eigenvalue spectrum.
- Average deviation for valence orbital eigenvalues and experimental ionization potentials is approximately 0.5 eV.
- Deviation for core orbitals is within 2 eV.
- These improvements are achieved with a minimal increase in total energy.
Conclusions:
- The proposed hybrid method offers a significant improvement in predicting electronic structure.
- It provides accurate ionization potentials and eigenvalue spectra.
- The method balances accuracy with computational cost effectively.
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