NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and machine learning techniques. Users can perform machine learning algorithms to find the ground-state of many-body Hamiltonians such as supervised learning of a given state and optimization of neural network states by using the variational Monte Carlo method.
Ab initio quantum Monte Carlo solver for both molecular and bulk electronic systems. By using the geminal/Pfaffian wavefunction with the Jastrow correlator as the trial wavefunction, users can perform highly accurate variational calculations, structural optimizations and ab initio molecular dynamics for both classical and quantum nuclei.
Python wrapper to manage jobs for the ab initio Monte Carlo package TurboRVB. By combining with a workflow management application, TurboWorkflows, users can perform high-throughput calculations based on TurboRVB.
A collection of shell scripts for installing open-source applications and tools for computational materials science to macOS, Linux PC, cluster workstations, and major supercomputer systems in Japan. Major applications are preinstalled to the nation-wide joint-use supercomputer system at Institute for Solid State Physics, University of Tokyo by using MateriApps Installer.
Debian Live Linux System that contains OS, editors, materials science application software, visualization tools, etc. An environment needed to perform materials science simulations is provided as a one package. By booting up on VirtualBox virtual machine, one can start simulations, such as the first-principles calculation, molecular dynamics, quantum chemical calculation, lattice model calculation, etc, immediately.
An open-source application for electronic structure calculation based on the diffusion Monte Carlo method. By using output of other packages of first-principles quantum-chemical calculation, this package performs electronic structure calculation with high accuracy. Although its computational cost is high, various physical quantities can be evaluated very accurately. It implements an efficient parallelization algorithm, and supports massively parallel computing.
A low-energy solver for a wide ranger of quantum lattice models (multi-orbital Hubbard model, Heisenberg model, Kondo-lattice model) by using variational Monte Carlo method. User can obtain high-accuracy wave functions for ground states of above models. Users flexibly choose the correlation factors in wavefunctions such as Gutzwiller, Jastrow, and doublon-holon binding factors and optimize more the ten thousand variational parameters. It is also possible to obtain the low-energy excited states by specifying the quantum number using the quantum number projection.
An open-source application for high-accuracy electronic-state calculation based on the variational Monte Carlo method and the diffusion Monte Carlo method. Although its computational cost is high, physical properties of atoms and small molecules in the ground states and excited states are calculated with very high accuracy. Includes an application program that generates input files from output of other packages for quantum chemical calculation, such as GAMESS, Gaussian, etc.
QMCPACK is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code. Its main applications are electronic structure calculations of molecular, quasi-2D and solid-state systems. Variational Monte Carlo (VMC), diffusion Monte Carlo (DMC), orbital space auxiliary field QMC (AFQMC) and a number of other advanced QMC algorithms are implemented.