activity
20162026
most citedMessage-Passing Neural Quantum States for the Homogeneous Electron Gas

48 citations · 85 across the 9 of their papers we have counts for

collaborators

9 papers

nucl-th2026

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…

nucl-th2026

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…

nucl-th2024

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.…

cond-mat.quant-gas2023★ 4 cited

Neural-network quantum states for ultra-cold Fermi gases

Jane Kim, Gabriel Pescia, Bryce Fore +5

Ultra-cold Fermi gases display diverse quantum mechanical properties, including the transition from a fermionic superfluid BCS state to a bosonic superfluid BEC state, which can be…

quant-ph2023★ 48 cited

Message-Passing Neural Quantum States for the Homogeneous Electron Gas

Gabriel Pescia, Jannes Nys, Jane Kim +2

We introduce a message-passing-neural-network-based wave function Ansatz to simulate extended, strongly interacting fermions in continuous space. Symmetry constraints, such as cont…

nucl-th2022★ 1 cited

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…

cond-mat.mes-hall2022★ 8 cited

Efficient Solutions of Fermionic Systems using Artificial Neural Networks

Even M. Nordhagen, Jane M. Kim, Bryce Fore +2

We discuss differences and similarities between variational Monte Carlo approaches that use conventional and artificial neural network parameterizations of the ground-state wave fu…

nucl-th2017★ 14 cited

Evolution of Charge Fluctuations and Correlations in the Hydrodynamic Stage of Heavy Ion Collisions

Scott Pratt, Jane Kim, Chris Plumberg

Charge fluctuations for a baryon-neutral quark-gluon plasma have been calculated in lattice gauge theory. These fluctuations provide a well-posed rigorous representation of the qua…

nucl-th2016★ 10 cited

Determining Transport Coefficients for a Microscopic Simulation of a Hadron Gas

Scott Pratt, Alexander Baez, Jane Kim

Quark-Gluon plasmas produced in relativistic heavy-ion collisions quickly expand and cool, entering a phase consisting of multiple interacting hadronic resonances just below the QC…