This is a structure analysis program for solutes and solvents, based on the statistical mechanics theory of liquids. The program determines the solvent density distribution surrounding the solute, and calculates various physical values such as the solvation free energy, compressibility, and partial molar volume. The program implements a parallelized fast Fourier transform routine for large-scale parallel computing, and can analyze molecular functions such as the ligand binding affinity of proteins, that would be difficult using other methods.
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.
RSDFT is an ab-initio program with the real-space difference method and a pseudo-potential method. Using density functional theory (DFT), this calculates electronic states in a vast range of physical systems: crystals, interfaces, molecules, etc. RSDFT is suitable for highly parallel computing because it does not need the fast Fourier transformation. By using the K-computer, this program can calculate the electronic states of around 100,000 atoms. The Gordon Bell Prize for Peak-Performance was awarded to RSDFT in 2011.
RSPACE is a first-principles code package based on a real-space finite-difference pseudo-potential method. It computes electronic states with high-speed and high precision in aperiodic systems of surfaces, solid interfaces, clusters, nanostructures, and so forth. It provides large-scale computing for semiconductor devices of nanostructure surface and interface reactions, calculation of transport properties in semi-infinite boundary conditions, and a massively parallel computing using the space partitioning method.
An open-source application for the first-principles calculation based on the all-electron method with localized bases. By adopting the full-potential LMTO method, high-speed electronic state calculation can be performed with a less number of bases compared with the standard all-electron method. There is no restriction on symmetries as in the LMTO-ASA method, and spin polarization and spin-orbit interaction can also be treated.
FORTRAN-based software package developed by the Behler Group for implementing Behler-Parinello neural network potentials. Potentials can be constructed, evaluated, and used for molecular dynamics simulations using LAMMPS. The newest generation of neural network potentials that take into account long-range electrostatic interactions are implemented.
Photo-excited electron dynamics simulator based on time-dependent density functional theory using real-time, real-space grids. It can perform calculations of linear photo-response and nonlinear photo-response to pulse radiation in a variety of systems including isolated systems, periodic systems, interfaces/surfaces, etc. It can perform massively parallel calculations in systems consisting of thousands of atoms, and it can also perform multiscale simulation of electron-electromagnetic field-coupled dynamics.
An open-source library for data mining and data analysis. This package implements various methods of machine learning such as supervised learning (data classification, data regression, etc.), unsupervised learning (data clustering, etc.), and data pre-processing. This package is implemented on Python numerical libraries, NumPy and Scipy, and supports parallel computation.
An open-source application for first-principles calculation utilizing pseudo-potentials and atom-localized basis sets. This application is capable of performing electronic structure calculations, structural relaxation, and molecular dynamics in a wide range of systems based on density functional theory. By adopting atom-localized basis sets, it realizes high-speed electronic calculation and linear-scaling in suitable computer systems. It can also perform electronic conductance calculations based on non-equilibrium Green’s function method.
Software package to implement Behler-Parinello neural network potentials. Potentials can be trained from structure-energy/ interatomic forces/stress data, and molecular dynamics calculations using LAMMPS can also be performed using learned potentials. A prediction uncertainty measure can also be calculated simultaneously.