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Ab initio study of Li7 with coupled mass partitions

Jakub Herko*

Konstantinos Kravvaris and Sofia Quaglioni

Petr Navrátil

Guillaume Hupin

Mark A. Caprio

  • TRIUMF, 4004 Wesbrook Mall, Vancouver, British Columbia, Canada V6T 2A3 and University of Victoria, 3800 Finnerty Road, Victoria, British Columbia, Canada V8P 5C2

  • *Contact author: jherko@triumf.ca

Phys. Rev. C 114, 044613 – Published 13 October, 2026

DOI: https://doi.org/10.1103/gyg8-q19s

Abstract

Background: Lithium is of broad interest in nuclear astrophysics, fusion energy research, and nuclear technology. From a theoretical perspective, the nucleus Li7 presents a remarkable challenge, as its bound and resonant states can exhibit contributions from both the He4 + H3 cluster configuration and configurations involving a neutron or proton coupled to a Li6 or He6 core, respectively.

Purpose: We aim to achieve a unified ab initio description of bound-state and continuum properties of Li7 by explicitly including simultaneously the coupled mass/charge partitions He4 + H3, Li6 + n, and He6 + p. Specifically, we investigate the effect of interpartition coupling on the spectrum of Li7 and calculate cross sections for the Li6(n,p)He6, He6(p,n)Li6, and He6(p,t)He4 reactions.

Method: We employ the no-core shell model with continuum for the first time in a calculation that couples three mass/charge partitions of the aggregate nucleus Li7, using a chiral nucleon-nucleon interaction as input.

Results: The calculated spectrum reproduces all the experimentally observed states of Li7 in the correct order and predicts additional resonances. The calculation also reproduces the overall energy dependence of the Li6(n,p)He6 cross section. Improved agreement with measured cross sections is obtained after phenomenological adjustment of resonance energies.

Conclusions: The present results show that coupling the relevant mass/charge partitions is important for a consistent description of the Li7 spectrum and reaction cross sections, and offers a useful framework for interpreting existing data and guiding future measurements.

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