An application for quantum chemical calculation based on DFTB (Density Functional based Tight Binding). This application performs structure
optimization and molecular dynamics by the DFTB force field as well as ordinary energy calculation, and implements parallel computing by OpenMP. A tool for visualization of molecular orbitals and an extended versions supporting MPI parallel computation or electron transport calculation by the nonequilibrium Green’s function method are also
available.
An application for first-principles calculation by the joint-DFT method based on a plane-wave basis. By implementation of the joint-DFT method, this application realizes a good convergence for electronic state calculation of molecules in liquid, particular for charged systems. This application is written by C++11, and supports GPU calculation by CUDA. This application also supports diffusive Monte Carlo simulation in cooperation with CASINO.
Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform written in Python. Users can perform mean-field and post-mean-field methods with standard Gaussian basis functions. This package also provides several interfaces to other software such as BLOCK and Libxc.
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.
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.
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.
An open-source application for first-principles molecular dynamics simulation based on pseudo-potential and plane-wave basis set. This application enables accurate molecular dynamics by density functional theory and Car-Parrinello method. It also supports structure optimization, Born-Oppenheimer molecular dynamics, path-integral molecular dynamics, calculation of response functions, the QM/MM method, and excited-state calculation.
A collection of software tools for molecular dynamics calculations. Various interatomic potentials and tight binding models are implemented, and numerous external applications can be invoked. It also supports training and evaluation of GAP (Gaussian Approximation Potential), which is a form of machine learning potential.
AkaiKKR is a first-principles all-electron code package that calculates the electronic structure of condensed matters using the Green’s function method (KKR). It is based on the density functional theory and is applicable to a wide range of physical systems. It can be used to simulate not only periodic crystalline solids, but also used to calculate electronic structures of impurity systems and, by using the coherent potential approximation (CPA), random systems such as disordered alloys, mixed crystals, and spin-disordered systems.
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.