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Nuclei with up to $\boldsymbol{A=6}$ nucleons with artificial neural network wave functions

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arxiv 2108.06836 v1 pith:S7FTOJAJ submitted 2021-08-15 nucl-th cond-mat.dis-nnquant-ph

classification nucl-thcond-mat.dis-nnquant-ph
keywords nucleiartificialfunctionsneuralnucleonswaveableaccurate
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abstract

The ground-breaking works of Weinberg have opened the way to calculations of atomic nuclei that are based on systematically improvable Hamiltonians. Solving the associated many-body Schr\"odinger equation involves non-trivial difficulties, due to the non-perturbative nature and strong spin-isospin dependence of nuclear interactions. Artificial neural networks have proven to be able to compactly represent the wave functions of nuclei with up to $A=4$ nucleons. In this work, we extend this approach to $^6$Li and $^6$He nuclei, using as input a leading-order pionless effective field theory Hamiltonian. We successfully benchmark their binding energies, point-nucleon densities, and radii with the highly accurate hyperspherical harmonics method.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Medium-mass nuclei with neural quantum states

    nucl-th 2026-07 conditional novelty 6.5 of 10

    Pfaffian-Jastrow neural quantum states yield ground-state energies and charge radii for nuclei up to A=58, with weak p-wave terms reducing average energy error to ~3% while revealing Hamiltonian sensitivity and A^3 scaling.

  2. A renormalizable theory for not-so-light nuclei

    nucl-th 2025-05 conditional novelty 6.0 of 10

    An improved effective field theory with artificial interaction ranges yields stable, cutoff-independent ground-state energies for 6Li, 12C, and 16O for the first time.

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