An application for prediction of stable and metastable structures from a chemical composition. This application applies particle swarm optimization to predict material structures from results of the first-principles calculation by external packages (VASP, CASTEP, Quantum Espresso, GULP, SIESTA, CP2k). It has been applied to predict not only three-dimensional crystal structures, but also those of clusters and surfaces.
CCCM is a high-order CCM (coupled cluster method) code for lattice spin systems. It is possible to obtain the ground state and its energy of quantum spin systems in two or three dimensions.
CrySPY is a crystal structure prediction tool by utilizing first-principles calculations and a classical MD program. Only by inputting chemical composition, crystal structures can be automatically generated and searched. In ver. 0.6.1, random search, Bayesian optimization, and LAQA are available as searching algorithms. CrySPY is interfaced with VASP, Quantum ESPRESSO, and LAMMPS.
An open-source application for visualization of many-particle systems. With simple operation by graphical user interface (GUI) or by command line, this application can visualize particle positions obtained from molecular dynamics simulation as well as three-dimensional scalar quantities such as potential energies. It supports various display options on kinds and shapes of particles, and can also visualize bond formation between particles.
GPU library for pdgemm and pzgemm, which are functions of matrix-matrix operations in ScaLAPACK.
A general-purpose application for molecular dynamics simulation equipped with many tools. This package was originally developed for biomolecules (peptides, proteins, nuclear acids, etc.), and the current version can perform molecular dynamics simulation for various systems such as solutions, crystals, membranes, and so on. It supports several sampling methods and calculation of free energy. It also supports various computing environments including both serial and parallel computers.
An open-source library for machine learning. Various functions on machine learning/deep learning are implemented in this package. Using flexible user-friendly description, various types of networks from simple to complex ones can be implemented. GPGPU parallel computation based on CUDA is also supported.
Program libraries for alloy modeling analysis using a cluster expansion method. Energy of alloy systems evaluated by other electronic state calculation libraries is used as an input, and atomic configuration effects are evaluated with the accuracy of a first principles calculation. Ground state structures, evaluation of thermodynamic quantities, equilibrium diagrams, disordering by temperature, etc. can be calculated with high accuracy.
An open-source library for machine learning. Various functions on deep learning based on neural network can be used by this package. This package is especially customised for image identification, and a number of sample codes are prepared. Users can also use pre-trained models, which are open in Caffe Model Zoo. Since this package is written in C++, high-speed operation is realised.
A Python framework for easy creation, manipulation and optimization of quantum algorithms for NISQ (Noisy Intermediate Scale Quantum Computer). A simulator for the quantum processor in the Xmon architecture provided by Google has also been supported.