PHYSBO is a Python library for researchers mainly in the materials science field to perform fast and scalable Bayesian optimization based on COMBO (Common Bayesian Optimization). Users can search the candidate with the largest objective function value from candidates listed in advance by using machine learning prediction. PHYSBO can handle a larger amount of data compared with standard implementations such as scikit-learn.
An ab-initio calculation package for X-ray spectrum analysis. X-ray spectra such as XAFS, XANES, etc. are predicted theoretically by multiple-scattering calculations based on real-space Green’s function formalism. A graphical user interface is provided. The license is provided for a fee for both non-profit and commercial users.
A collection of C++ interfaces for simulation of mesoscale properties based on grid data. By using provided header files, one can easily construct programs for simulation of various phenomena such as solidification, crystal growth, and spinodal decomposition, based on a Monte Carlo method, cellar automaton, and a phase-field method. This interface supports parallel computing by MPI, and also provides converters of output files for visualization software such as ParaView.
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.
Software package that implements moment tensor potentials. Potentials can be trained and used for molecular dynamics calculations using LAMMPS. Active learning combined with molecular dynamics calculations is also available.
An open-source application for simulation based on the density-matrix renormalization group (DMRG). This application can perform high-speed calculation of low-dimensional quantum systems with high accuracy. It implements generic programming techniques in the C++ language, and can easily extend simulation to new models and geometries. It is developed putting emphasis on user-friendly interfaces and low dependences on environments.
An open-source program package for first-principles calculation based on a mixed augmented plane wave method (the PMT method). For various physical systems, this package performs electronic structure calculation and structure optimization by LDA, GGA, LDA+U and so on. It further can treat quasi-particle excitation with high accuracy by the quasi-particle self-consistent GW method. It implements several original methods not included in other program packages, and is maintained by the version control system, Git.
An exact diagonalization package for a wide range of quantum lattice models (e.g. multi-orbital Hubbard model, Heisenberg model, Kondo lattice model). HΦ also supports the massively parallel computations. The Lanczos algorithm for obtaining the ground state and thermal pure quantum state method for finite-temperature calculations are implemented. In addition, dynamical Green’s functions can be calculated using Kω, which is a library of the shifted Krylov subspace method. It is possible to perform simulations for real-time evolution from ver. 3.0.
Payware for first-principles quantum chemical calculation. This application performs molecular orbital calculation based on Hartree-Fock approximation, density functional method, and post-HF methods such as MP, f12, multi-configuration SCF, and coupled cluster method. It also implements calculation by path-integral instanton, quantum Monte Carlo, and density-matrix renormalization group method.
2DMAT is a framework for applying a search algorithm to a direct problem solver to find the optimal solution. In version 1.0, for solving a direct problem, 2DMAT offers the wrapper of the solver for the total-reflection high-energy positron diffraction (TRHEPD) experiment. As algorithms, it offers the Nelder-Mead method, the grid search method, the Bayesian optimization method, and the replica exchange Monte Carlo method. Users can define original direct problem solvers or the search algorithms.