Papers
A non-comprehensive list of some papers that used NetKet.
If your paper or preprint uses NetKet, feel free to open a PR at the netket/netket.org repository adding it. You just need to create a file that looks like this example.
Simple Fermionic backflow states via a systematically improvable tensor decomposition
Authors: Massimo Bortone, Yannic Rath, George H. Booth
Empirical sample complexity of neural network mixed state reconstruction
Authors: Haimeng Zhao, Giuseppe Carleo, Filippo Vicentini
Impact of conditional modelling for a universal autoregressive quantum state
Authors: Massimo Bortone, Yannic Rath, George H. Booth
Efficiency of neural quantum states in light of the quantum geometric tensor
Authors: Sidhartha Dash, Luca Gravina, Filippo Vicentini, Michel Ferrero, Antoine Georges
A simple linear algebra identity to optimize large-scale neural network quantum states
Authors: Riccardo Rende, Luciano Viteritti, Lorenzo Bardone, Federico Becca, Sebastian Goldt
Journal: Communication Physics 7, 260
Year: 2023
Cite: BibTex
ArXiV: 2310.05715
Code: Link to Repository
Variational Embeddings for Many Body Quantum Systems
Authors: Stefano Barison, Filippo Vicentini, Giuseppe Carleo
Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution
Authors: Alessandro Sinibaldi, Clemens Giuliani, Giuseppe Carleo, Filippo Vicentini
High-accuracy variational Monte Carlo for frustrated magnets with deep neural networks
Authors: Christopher Roth, Attila Szabó, Allan H. MacDonald
NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems
Authors: Filippo Vicentini, Damian Hofmann, Attila Szabó, Dian Wu, Christopher Roth, Clemens Giuliani, Gabriel Pescia, Jannes Nys, Vladimir Vargas-Calderón, Nikita Astrakhantsev, Giuseppe Carleo
Journal: SciPost Physics Codebases
Year: 2022
Cite: BibTex
ArXiV: 2112.10526
Code: Link to Repository
Positive-definite parametrization of mixed quantum states with deep neural networks
Authors: Filippo Vicentini, Riccardo Rossi, Giuseppe Carleo