Efficient excitations and spectra within a perturbative renormalization approach

Abstract

We present a self-consistent approach for computing the correlated quasiparticle spectrum of charged excitations in iterative $\mathcal{O}[N^5]$ computational time. This is based on the auxiliary second-order Green's function approach [O. Backhouse \textit{et al.}, JCTC (2020)], in which a self-consistent effective Hamiltonian is constructed by systematically renormalizing the dynamical effects of the self-energy at second-order perturbation theory. From extensive benchmarking across the W4-11 molecular test set, we show that the iterative renormalization and truncation of the effective dynamical resolution arising from the $2h1p$ and $1h2p$ spaces can substantially improve the quality of the resulting ionization potential and electron affinity predictions compared to benchmark values. The resulting method is shown to be superior in accuracy to similarly scaling quantum chemical methods for charged excitations in EOM-CC2 and ADC(2), across this test set, while the self-consistency also removes the dependence on the underlying mean-field reference. The approach also allows for single-shot computation of the entire quasiparticle spectrum, which is applied to the benzoquinone molecule and demonstrates the reduction in the single-particle gap due to the correlated physics, and gives direct access to the localization of the Dyson orbitals.

9 pages, 4 figures

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• Excitations and spectra from equilibrium real-time Green's functions
• Equivariant neural network for Green's functions of molecules and materials
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• Complex Absorbing Potential Green's Function Methods for Resonances
• Diagrammatic theory of the irreducible coupled-cluster self-energy
• Parquet theory for molecular systems: Formalism and static kernel parquet approximation
• Scalable and predictive spectra of correlated molecules with moment truncated iterated perturbation theory