NetKet
@NetKetOrg
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NetKet is an open-source project for the study of many-body quantum systems with artificial neural networks and machine learning techniques.
Joined April 2018
The NetKet team is proud to present a new pre-print, describing the main features, theory, benchmarks and more of JAX-based NetKet 3! Supported by @cqs_lab, contributors from @EPFL_en @maxplanckpress @UniofOxford @UTAustin @UNALOficial @UZH_en, here:
arxiv.org
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 for their...
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Among others, this release includes BoseHubbard in Jax, generalized Slater determinants, a stable Parallel Tempering sampler, timing utilities, and much more! 2/2
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NetKet 3.12 is out, check the release notes here https://t.co/HSODWzZQtj ! Special thanks to @philipVinc @Polytechnique and Clemens Giuliani @cqs_lab @EPFL_en for the hard work to make this possible. 1/2
github.com
Machine learning algorithms for many-body quantum systems - netket/netket
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🌟🚀 2023's Top Papers on Neural Quantum States! A year of many innovative approaches blending ML with quantum science. Here are my top picks: 1. Fast Quantum Natural Gradient (SR), our favorite optimizer, now scaling linearly for small batch sizes https://t.co/YYKKZrPTjB 2.
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NetKet 3.10 is out. Many new features, bug fixes and improvements! Full release notes here
github.com
The highlights of this version are a new experimental driver to optimise networks with millions of parameters using SR, and introduces new utility functions to convert a pyscf molecule to a netket ...
@NetKetOrg 3.10 is out! This release is probably our largest to date, and the highlights include a blazing-fast natural gradient- VMC optimiser that works with millions of NN parameters, PySCF integration to build the electronic hamiltonians, better documentation and more!
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We had a very productive @cqs_lab group retreat last week, enjoying the beauty of southern Italy (Greek temples, pizzas, and buffaloes included) and discussing quantum physics, @NetKetOrg and more!
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It's time for another brand new @NetKetOrg tutorial! This week, thanks to @pgabbo0 of @cqs_lab @EPFL, we explore bosonic systems in continuous space: first, a 3D harmonic oscillator and then 1D confided particles with Gaussian interactions, using a DeepSet NQS
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Started in 2018, NetKet @NetKetOrg was the first open-source library for machine learning and many-body quantum physics ever released, and we are proud to see it being used by an increasing number of researchers! With version 3 (released in 2021 thanks to the efforts of many and
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2022 has been a fantastic year for @cqs_lab: we deployed neural quantum states to accurately study many-body systems at vastly different scales, from superfluid Helium to Neutron Stars; @NetKetOrg 3.0 was released; new hybrid ML-quantum algos were introduced. Stay tuned for 2023!
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Looks like Galactica knows how to use NetKet to train a neural quantum state, that's good news :) @NetKetOrg
https://t.co/KNXbdVGUhs
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The NetKet 3 manuscript is finally published in @scipost_dot_org Codebases (manuscript here https://t.co/CHy4rHxudU). Check the great thread below by our lead developer @philipVinc to learn more! 👇👇
The @NetKetOrg 3 manuscript has been published in @SciPost_Physics Codebases! https://t.co/Ie1IsGoM4C This goes in tandem with the new version 3.5 release! Supported by @gppcarleo @cqs_lab, contributors from @EPFL_en @maxplanckpress @UniofOxford @UTAustin @UNALOficial @UZH_en
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@philipVinc from @EPFL is introducing @NetKetOrg, taking a Neural Network approach to quantum physics problems.
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Check this out, NetKet is part of the #UnitaryHack 2022 !
#UnitaryHack 2022 (June 3-17) Hackathon Project‼️ Netket 🧰 (@NetKetOrg): The Machine-Learning toolbox for Many-Body Quantum Physics: Neural-Network Quantum states and much more. Learn more: https://t.co/x7mOk0842A Sign up now!➡️:
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Now happening in Toulouse: @philipVinc and Damian Hofmann, the perfect duo to give a NetKet tutorials on ground state properties @NetKetOrg @cqs_lab @EPFL_en @maxplanckpress
https://t.co/bZ7keyjjov
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CONF: me and @JannesNys (@cqs_lab) are organising a workshop on Quantum and Classical Variational algorithms for quantum systems. "Variational Learning Quantum Matter" will be hosted at the @EPFL_en Bernoulli Center in Lausanne, 4-8 July 2022. https://t.co/5T6FZaKb2A
mlquantum.org
Mini-conference at the intersection between classical and quantum variational algorithms to study quantum many-body systems. 5 days of focused talks and discussions among the 50 participants on a...
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Glad to advertise a summer school (April 4-8) on Machine Learning techniques for Quantum Many-Body Physics, in Toulouse, France. The school will feature several lectures and tutorials on NetKet. Deadline for registrations is March 8! https://t.co/dn4m6wlk6K
@gppcarleo @philipVinc
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vote now!
@NetKetOrg retweet me: How would you like the time-evolution driver of NetKet to be named? It will work with real/imaginary time unitary dynamics (TDVP), lindblad dynamics, variational states + monte-carlo sampling, variational states without sampling.
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Live tutorial on @NetKetOrg (especially on symmetries and unitary dynamics) by @philipVinc
https://t.co/UVtoJyCIBL (3/4)
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mpi4jax is the library that netket uses to exploit multi CPU-GPU parallelism under MPI and XLA/Jax. Developed by netket's lead developer @philipVinc @cqs_lab and by Dion Häfner @uni_copenhagen, it is now published in JOSS (@JOSS_TheOJ)
joss.theoj.org
Häfner et al., (2021). mpi4jax: Zero-copy MPI communication of JAX arrays. Journal of Open Source Software, 6(65), 3419, https://doi.org/10.21105/joss.03419
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