12 citations · 12 across the 10 of their papers we have counts for
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Medium-mass nuclei with neural quantum states
Bryce Fore, Jane Kim, Alessandro Lovato +1
We compute ground-state energies and charge radii of light- to medium-mass nuclei with up to nucleons, leveraging a variational Monte Carlo method based on Pfaffian-Jastrow…
Tomography of Atomic Nuclei
Noemi Rocco, Carlo Graziani, Alessandro Lovato +2
We carry out continuum quantum Monte Carlo calculations of the quantum-mechanical Wigner distribution functions of selected nuclei, up to O. These distributions provide a fo…
Quantum Monte Carlo calculation of in the superallowed beta decay of C
Maria Piarulli, R. B. Wiringa, Alessandro Lovato +2
We perform an ab initio quantum Monte Carlo calculation of the isospin-symmetry-breaking correction to the superallowed decay of . Using both phenomenologic…
Neural Quantum States in Non-Stabilizer Regimes: Benchmarks with Atomic Nuclei
James W. T. Keeble, Alessandro Lovato, Caroline E. P. Robin
As neural networks are known to efficiently represent classes of tensor-network states as well as volume-law-entangled states, identifying which properties determine the representa…
Neural-network quantum states for the nuclear many-body problem
Alessandro Lovato, Giuseppe Carleo, Bryce Fore +4
A long-standing goal of nuclear theory is to explain how the structure and dynamics of atomic nuclei and neutron-star matter emerge from the underlying interactions among protons a…
Nuclear responses with neural-network quantum states
Elad Parnes, Nir Barnea, Giuseppe Carleo +3
We introduce a variational Monte Carlo framework that combines neural-network quantum states with the Lorentz integral transform technique to compute the dynamical properties of se…
Investigating the crust of neutron stars with neural-network quantum states
Bryce Fore, Jane Kim, Morten Hjorth-Jensen +1
An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm and 0.…
Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks
Joanna E. Sobczyk, Noemi Rocco, Alessandro Lovato
We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quanti…
Static and dynamic properties of atomic nuclei with high-resolution potentials
Alex Gnech, Alessandro Lovato, Noemi Rocco
We compute ground-state and dynamical properties of He and O nuclei using as input high-resolution, phenomenological nucleon-nucleon and three-nucleon forces that are lo…
High-resolution momentum distributions from low-resolution wave functions
A. J. Tropiano, S. K. Bogner, R. J. Furnstahl +3
Nucleon momentum distributions calculated with a common one-body operator vary with the resolution scale (and scheme) of the Hamiltonian used. For high-resolution potentials such a…