Multi-reference many-body perturbation theory for nuclei

In spite of missing dynamical correlations, the projected generator coordinate method (PGCM) was recently shown to be a suitable method to tackle the low-lying spectroscopy of complex nuclei. Still, describing absolute binding energies and reaching high accuracy eventually requires the inclusion of dynamical correlations on top of the PGCM. In this context, the present work discusses the first realistic results of a novel multi-reference perturbation theory (PGCM-PT) that can do so within a symmetry-conserving scheme for both ground and low-lying excited states. First, proof-of-principle calculations in a small (e(max) = 4) model space demonstrate that exact binding energies of closed-(O-16) and open-shell (O-18, Ne-20) nuclei are reproduced within 0.5-1.5% at second order, i.e. through PGCM-PT(2). Moreover, profiting from the pre-processing of the Hamiltonian via multi-reference in-medium similarity renormalization group transformations, PGCM-PT(2) can reach converged values within smaller model spaces than with an unevolved Hamiltonian. Doing so, dynamical correlations captured by PGCM-PT(2) are shown to bring essential corrections to low-lying excitation energies that become too dilated at leading order, i.e., at the strict PGCM level. The present work is laying the foundations for a better understanding of the optimal way to grasp static and dynamical correlations in a consistent fashion, with the aim of accurately describing ground and excited states of complex nuclei via ab initio many-body methods.

Automated summary

This article presents the first realistic results of a novel multi-reference perturbation theory (PGCM-PT) that can accurately describe the ground and low-lying excited states of complex nuclei within a symmetry-conserving scheme. The study demonstrates that PGCM-PT(2) can reproduce the exact binding energies of closed and open-shell nuclei with high accuracy and can capture essential corrections to low-lying excitation energies by including dynamical correlations.