An open source C++ library designed for the development of tensor network algorithms. The goal of this library is to provide basic tensor operations with an easy-to-use interface, and it also provides a Network class that handles the graphical representation of networks. A wrapper for calling it from Python is also provided.
Application for specifying and simulating lattice kinetic Monte Carlo models. It has been developed in the context of simulating heterogeneous catalysis. Models can be specified using provided python APIs or through a simple GUI.
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.
A free software library for numerical diagonalization of quantum spin systems. Although the programs are based on TITPACK, they have been completely rewritten in C/C++ and several extensions have been added. It can handle, for example, the Heisenberg model, the Hubbard model, and the t-J model. This library supports dimension reduction of matrices exploiting symmetries, and it can run in parallel computing environments.
A Python library for simulating strongly correlated quantum systems using tensor networks. The goal is to make the algorithms readable and easy to use for beginners, and also powerful and fast for experts. Simple sample code and toy code to illustrate TEBD and DMRG are also provided.
An open-source application for molecular dynamics simulation of biomolecules. This application is optimized for massive parallel computing environments such as the K-computer, and can perform high-speed molecular dynamical simulation of proteins and biomolecules. This application supports both all atoms calculation and coarse-grained model calculation, and can treat extended ensemble such as a replica exchange method. This code is released under GPL license.
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.
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.
An application program for lattice dynamics calculation of molecules, surfaces, and solids in various boundary conditions. It lays emphasis on analytic calculation of lattice dynamics while it can perform molecular dynamics simulation as well. It supports various force fields to treat ionic materials, organic materials, and metals. It also implements analytic derivatives of the second and third order for many force fields.
An open source library for implementing tensor networks. It is developed based on TensorFlow and is designed to be easily used by experts in the field of machine learning as well as in the field of physics. In addition to TensorFlow, it includes wrappers for JAX, PyTorch, and Numpy.