COMmon Bayesian Optimization Library (COMBO) is an open source python library for machine learning techniques. COMBO is amenable to large scale problems, because the computational time grows only linearly as the number of candidates increases. Hyperparameters of a prediction model can be automatically learned from data by maximizing type-II likelihood.
LIQ𝑈𝑖⏐〉is a software design architecture for quantum computing. It includes a programming language designed for quantum algorithms. By using LIQ𝑈𝑖⏐〉, users can design quantum circuits and perform simulations such as quantum teleportation and quantum chemistry.
An open-source application for atomic structure analysis from powder diffraction data. This application can calculate atomic coordinates, valence sums, and chemical bonds from diffraction data of crystals, nanostructures, and amorphous materials. It is written in Python, and realizes multi-functional fitting and flexible data analysis.
A set of routines for real-symmetric dense eigenproblems in supercomputers or massively parallel machines. Both of standard and general eigenproblems are supported. A fast computation is achieved by optimal hybrid solvers among eigenproblem libraries of ELPA, EigenExa and ScaLAPACK. The package includes a mini-appli that can be used in a benchmark test.
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.
An application for data analysis of X-ray absorption fine structure (XAFS). By interactive operation using a command line, experimental data of XAFS can be analyzed by various analysis methods. This application also supports various useful functions such as high-speed Fourier analysis, fitting in the radial/k-space coordinates, and data plotting.
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.
An application for visualization of biopolymers. This application can visualize biopolymers by using its original command line and graphical user interface, more than 600 settings for visualization, and more than 20 visualization schemes. This application also supports more than 30 file formats such as PDB and multi-SDF, and can utilize sophisticated visualization methods such as the ray tracing.
A unified wrapper library for sequential and parallel versions of eigenvalue solvers. Sequential versions of dense-matrix diagonalization (LAPACK), parallel versions of dense-matrix diagonalization (EigenExa, ELPA, ScaLAPACK, etc.), and sequential/parallel versions of sparse-matrix diagonalization (SLEPc, Trilinos/Anasazi, etc.) can be installed quickly, and can be called from user’s program easily. Physical quantities written by eigenvalues or eigenvectors can also be evaluated by both sequential and parallel computation.
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.