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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…
Dilute neutron star matter from neural-network quantum states
Bryce Fore, Jane M. Kim, Giuseppe Carleo +2
Low-density neutron matter is characterized by fascinating emergent quantum phenomena, such as the formation of Cooper pairs and the onset of superfluidity. We model this density r…
Hidden-nucleons neural-network quantum states for the nuclear many-body problem
A. Lovato, C. Adams, G. Carleo +1
We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrödinger eq…
Nuclei with up to nucleons with artificial neural network wave functions
Alex Gnech, Corey Adams, Nicholas Brawand +3
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-bod…
Variational Monte Carlo calculations of nuclei with an artificial neural-network correlator ansatz
Corey Adams, Giuseppe Carleo, Alessandro Lovato +1
The complexity of many-body quantum wave functions is a central aspect of several fields of physics and chemistry where non-perturbative interactions are prominent. Artificial neur…