Nuclei with Up to A = 6 Nucleons with Artificial Neural Network Wave Functions

Nuclei with Up to A = 6 Nucleons with Artificial Neural Network Wave Functions

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 Schrödinger equation involves non-trivial difficulties, due to the non-perturbative nature and strong spin-isospin dep...

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Veröffentlicht in:Few-body systems 2021-12, Vol.63 (1)
Hauptverfasser: Gnech, Alex, Adams, Corey, Brawand, Nicholas, Carleo, Giuseppe, Lovato, Alessandro, Rocco, Noemi
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ATOMIC AND MOLECULAR PHYSICS
NUCLEAR PHYSICS AND RADIATION PHYSICS
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container_issue 1
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container_title Few-body systems
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creator Gnech, Alex
Adams, Corey
Brawand, Nicholas
Carleo, Giuseppe
Lovato, Alessandro
Rocco, Noemi
description 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 Schrödinger 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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NUCLEAR PHYSICS AND RADIATION PHYSICS
title Nuclei with Up to A = 6 Nucleons with Artificial Neural Network Wave Functions
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