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.
The fragment molecular orbital (FMO) method can efficiently do quantum-mechanical calculations of large molecular systems by splitting the whole system into small fragments. The FMO program is distributed within quantum-chemical program suite GAMESS-US. FMO can provide various information regarding the structure and function of biopolymers, such as the interaction between a protein and a ligand.
A open-source application of first-principles calculation for the electronic structure, using the KKR method, a variant of Green’s function method. It is based on the density functional theory and is applicable to crystals and surfaces. The coherent potential approximation (CPA) is adopted, so it can handle not only periodic systems, but also disordered alloys. It can also handle spin-orbit interaction and non-collinear magnetism.
A low-energy solver for a wide ranger of quantum lattice models (multi-orbital Hubbard model, Heisenberg model, Kondo-lattice model) by using variational Monte Carlo method. User can obtain high-accuracy wave functions for ground states of above models. Users flexibly choose the correlation factors in wavefunctions such as Gutzwiller, Jastrow, and doublon-holon binding factors and optimize more the ten thousand variational parameters. It is also possible to obtain the low-energy excited states by specifying the quantum number using the quantum number projection.
Open source software for building and using machine learning potentials based on E(3)-equivariant graph neural networks, which can be trained on output files of simulation codes that can be read by ASE. Molecular dynamics calculations with LAMMPS can be performed using the trained potentials.