An open-source application for ab initio quantum chemical calculation. This application performs electronic structure calculation of molecules by the Hartree-Fock, density functional, many-body perturbation, configuration interaction theories, and so on. Even though this application is freeware, it succeeds in maintaining high-quality and high-performance codes by active development, and has a number of world-wide users. It histrically shares core programs with GAMESS-UK.
An open-source application for molecular dynamics simulation of biomolecules. This application is optimized for massive parallel computing environments such as the K-computer, and can perform high-speed molecular dynamical simulation of proteins and biomolecules. This application supports both all atoms calculation and coarse-grained model calculation, and can treat extended ensemble such as a replica exchange method. This code is released under GPL license.
An application for evaluation of thermoelectric properties and its visualization. Seebeck coefficients and Peltier coefficients can be calculated from output of the first-principles applications, OpenMX and TranSIESTA. Obtained results as well as electron density and density of states can be visualized.
An open-source application for quantum chemical calculation. This package implements various methods for quantum chemical calculation such as Hartree-Fock approximation, density functional theory, coupled-cluster method, and CI (configuration interaction) method. The package is written in C++, and provides API for Python, by which users can perform for preparation of setting and execution of calculation.
BEEMs is a Bayesian optimization tool of Effective Models (BEEMs). In BEEMs, the quantum lattice model solver HΦ is used as a forward problem solver to compute the magnetisation curve based on the given Hamiltonian. The deviation between the obtained magnetisation curve and the target magnetisation curve is used as a cost function, and the Bayesian optimization library PHYSBO is used to propose the next candidate point of the Hamiltonian for searching the minimum cost function