282 citations · 940 across the 52 of their papers we have counts for
12 papers · 1 filter
Neural-Network Quantum States for Periodic Systems in Continuous Space
Gabriel Pescia, Jiequn Han, Alessandro Lovato +2
We introduce a family of neural quantum states for the simulation of strongly interacting systems in the presence of spatial periodicity. Our variational state is parameterized in…
NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems
Filippo Vicentini, Damian Hofmann, Attila Szabó +8
We introduce version 3 of NetKet, the machine learning toolbox for many-body quantum physics. NetKet is built around neural-network quantum states and provides efficient algorithms…
Fermionic Wave Functions from Neural-Network Constrained Hidden States
Javier Robledo Moreno, Giuseppe Carleo, Antoine Georges +1
We introduce a systematically improvable family of variational wave functions for the simulation of strongly correlated fermionic systems. This family consists of Slater determinan…
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…
Continuous-variable neural-network quantum states and the quantum rotor model
James Stokes, Saibal De, Shravan Veerapaneni +1
We initiate the study of neural-network quantum state algorithms for analyzing continuous-variable lattice quantum systems in first quantization. A simple family of continuous-vari…
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks
Dian Wu, Riccardo Rossi, Giuseppe Carleo
Efficient sampling of complex high-dimensional probability distributions is a central task in computational science. Machine learning methods like autoregressive neural networks, u…