Efficient excitations and spectra within a perturbative renormalization approach
Oliver J. Backhouse, George H. Booth

TL;DR
This paper introduces a self-consistent, perturbative renormalization approach for accurately computing charged excitation spectra with improved predictions over existing methods, while maintaining manageable computational costs.
Contribution
It develops a novel iterative renormalization technique within a second-order Green's function framework that enhances accuracy and removes reference dependence in quasiparticle spectrum calculations.
Findings
Improved ionization potential and electron affinity predictions.
Superior accuracy compared to EOM-CC2 and ADC(2) methods.
Demonstrated reduction in single-particle gap for benzoquinone.
Abstract
We present a self-consistent approach for computing the correlated quasiparticle spectrum of charged excitations in iterative 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 and 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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
