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Renormalization group approach to second-order Green's function theory
Joshua Krieger1, Johannes Tölle2
1Institute of Physical Chemistry, University of Münster, Corrensstraße 28/30, 48149 Münster, Germany; Center for Multiscale Theory and Computation, 48149 Münster, Germany; and International Graduate School BACCARA, 48149 Münster, Germany.
This study presents a novel method for creating a stable Fock matrix in self-consistent field calculations. The new approach improves accuracy for quasiparticle energies and dipole moments, avoiding common divergence issues.
Area of Science:
- Quantum Chemistry
- Computational Physics
- Many-Body Perturbation Theory
Background:
- Self-consistent field (SCF) calculations are fundamental in quantum chemistry.
- Standard methods like Møller-Plesset perturbation theory can suffer from divergences.
- Accurate prediction of electronic properties requires robust theoretical frameworks.
Purpose of the Study:
- To develop a new, regularized Fock matrix construction for SCF calculations.
- To improve the accuracy and stability of electronic structure calculations.
- To address divergence issues in perturbation theory.
Main Methods:
- Utilizing second-order perturbation theory and quasiparticle self-consistent second-order Green's function theory (GF2).
- Applying perturbative similarity renormalization group (SRG) theory for regularization.
- Introducing and optimizing three SRG-qsGF2 variants by tuning parameters.
Main Results:
- Developed three SRG-qsGF2 variants for accurate quasiparticle energy and dipole moment predictions.
- Demonstrated mitigation of divergence problems in electronic energy calculations.
- Showcased the effectiveness of the renormalized Fock matrix as an unperturbed Hamiltonian.
Conclusions:
- The proposed SRG-based Fock matrix construction offers a stable and accurate alternative for SCF calculations.
- This method enhances the reliability of quantum chemical predictions.
- The approach provides a pathway to overcome limitations of conventional perturbation theories.
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