AkaiKKR is a first-principles all-electron code package that calculates the electronic structure of condensed matters using the Green’s function method (KKR). It is based on the density functional theory and is applicable to a wide range of physical systems. It can be used to simulate not only periodic crystalline solids, but also used to calculate electronic structures of impurity systems and, by using the coherent potential approximation (CPA), random systems such as disordered alloys, mixed crystals, and spin-disordered systems.
A first principles calculation program using all electron mixture based approach. It targets broad physical systems such as isolated systems, surfaces and interfaces, and crystals, and it calculates all electronic states from core electrons to valence electrons. It deals with calculation methods such as the GW method, and also deals with parallel calculations. It can execute with high accuracy molecular dynamics calculations for electronic excited states based on time dependent density functional theory.
An open-source application for first-principles calculation based on the PAW method. By utilizing real-space or atom-localized basis sets, this application performs electronic structure calculation based on the density functional theory as well as the GW approximation. Simulations are set up using the interface provided by Atomic Simulation Environment (ASE). The code is written in C and python, and is available under GPL.
A program package for physical properties related to magnetism. This application can evaluate various physical quantities of magnetics such as crystal fields, magnetic structures, thermodynamic quantities (magnetization, specific heat, etc.), and magnetic excitation. This package can also perform fitting analysis of neutron diffraction experiments and resonant X-ray diffraction experiments, and is helpful to experimentalists.
Code for unfolding first-principles electronic energy bands calculated using supercells into the corresponding primary-cell Brillouin zone. It uses maximally-localized Wannier functions calculated using Wannier90.
An open-source application for quantum chemical calculation based on the density-matrix renormalization group (DMRG). For systems with a number of atomic orbitals, low-lying energy eigenvalues can be calculated in high accuracy of order of 1kcal/mol. This application is suitable especially to calculation of multi-orbital systems with one-dimensional topology such as chain-like or circular-like configuration of orbits.
An application for semi-empirical quantum chemistry calculation. Special emphasis is placed on molecular dynamics simulations, and is able to run efficiently on large-scale cluster computer systems using OpenMP/MPI hybrid parallelism. The code is still under development, but the source code is distributed freely under the GPL license.
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 open-source application for first-principles molecular dynamics based on a pseudopotential method using plane bases. This application can perform electronic-state calculation and molecular dynamics employing the Car-Parrinello method. It implements MPI parallelization, which enables us to perform efficient parallel computing in various environments including large-scale parallel computers. The program is written in C++, and is distributed in source form under the GPL license.
An open-source solver for the impurity problem based on the continuous-time quantum Monte Carlo method. Imaginary-time Green’s functions of the impurity Anderson model and the effective impurity model in the dynamical mean-field approximation can be calculated with high speed by using an efficient Monte Carlo algorithm. The main programs are written by C++, and can be called from Python scripts.