AMULET is a collection of tools for a first principles calculation of physical properties of strongly correlated materials. It is based on density functional theory (DFT) combined with dynamical mean-field theory (DMFT). Users can calculate physical properties of chemically disordered compounds and alloys within CPA+DMFT formalism.
Software framework for training a machine learning model to reproduce first-principles energies and then using the model to perform configurational sampling in disordered systems. It has been developed with an emphasis on multi-component solid-state systems such as metal and oxide alloys. At present, Quantum Espresso, VASP and OpenMX can be used as first-principles energy calculators, and aenet can be used to construct neural network potentials.
Open-source software for building computational physics applications. Common C++ auxiliary modules required for various methods in computational physics such as the quantum Monte Carlo method are prepared. This software helps to build reusable codes and to reduce development time for complex computational science applications. It also supports parallel programming based on MPI or OpenMP.
A set of tools for alloy theory analysis in combination with first-principles calculation packages. Free energy and thermodynamic phase diagrams of alloy systems are calculated by combining the cluster expansion method with Monte Carlo simulations. Interfaces with major first-principles code including Quantum Espresso, VASP, and ABINIT are provided.
An open-source impurity solver based on the quantum Monte Carlo method. Thermal equilibrium states of interacting impurity systems, such as the impurity Anderson model, can be evaluated by the continuous-time hybridization-expansion quantum Monte Carlo method. It can be used as a solver of effective impurity models derived from the dynamical mean-field theory (DMFT) and can deal with multi-orbital models. This package supports parallel computation by MPI and is developed based on the ALPSCore library.
aenet is software for atomic interaction potentials using artificial neural networks. Users can construct neural network potentials using structures of target materials and their energies obtained from first principle calculations. The generated potentials can be used to molecular dynamics or Monte Carlo simulations.
Payware for evaluation of electron transport based on nonequilibrium Green’s function. This application is descended from the SIESTA application, and can calculate electronic transport properties of bulk materials and molecules inserted between leads by performing electronic state calculation under a finite bias. One can choose either density functional method or semiempirical method, and can control external factors such as gate voltages. It also implements structure optimization and analysis of chemical reaction paths.
An open-source application of molecular modeling/editing for quantum chemical calculation. This application supports graphical user interface (GUI) for input-file preparation for software of quantum chemical calculation such as GAMESS, Gaussian, etc., and displays their results by reading output files. It can also make movies in the formats of vector graphics, POV-Ray, and so on.
Open source software for constructing the Allegro potential model based on E(3)-equivariant graph neural networks and using the potential model for molecular dynamics simulations. The code depends on NequIP and can be run in a similar manner. Allegro scales better than NequIP since it doesn’t rely on message passing and the architecture is strictly local with respect to atom-wise environments.