Renormalized Singles Green's Function in the T-Matrix Approximation for Accurate Quasiparticle Energy Calculation

TL;DR

This paper introduces a combined renormalized singles Green's function with the T-Matrix approximation to improve quasiparticle energy calculations, achieving higher accuracy and reduced dependence on density functional choices.

Contribution

The study develops the $G_{ ext{RS}}T_{ ext{RS}}$ method, integrating RS Green's functions into the T-Matrix approach, significantly enhancing quasiparticle energy predictions for molecular systems.

Findings

$G_{ ext{RS}}T_{ ext{RS}}$ outperforms $G_0T_0$ in accuracy.

Method reduces dependence on density functional approximations.

Accurately identifies spectral peaks and core level energies.

Abstract

We combine the renormalized singles (RS) Green's function with the T-Matrix approximation for the single-particle Green's function to compute quasiparticle energies for valence and core states of molecular systems. The $G_{\text{RS}}T_0$ method uses the RS Green's function that incorporates singles contributions as the initial Green's function. The $G_{\text{RS}}T_{\text{RS}}$ method further calculates the generalized effective interaction with the RS Green's function by using RS eigenvalues in the T-Matrix calculation through the particle-particle random phase approximation. The $G_{\text{RS}}T_{\text{RS}}$ method provides significant improvements over the one-shot T-Matrix method $G_0T_0$ as demonstrated in calculations for GW100 and CORE65 test sets. It also systematically eliminates the dependence of $G_{0}T_{0}$ on the choice of density functional approximations (DFAs). For valence states, the $G_{\text{RS}}T_{\text{RS}}$ method provides an excellent accuracy, which is better than $G_0T_0$ with Hartree-Fock (HF) or other DFAs. For core states, the $G_{\text{RS}}T_{\text{RS}}$ method correctly identifies desired peaks in the spectral function and significantly outperforms $G_0T_0$ on core level binding energies (CLBEs) and relative CLBEs, with any commonly used DFAs.