An open-source application for general-purpose quantum chemical calculation, laying emphasis on excited states and time evolution. It is based on time-dependent density functional theory (TDDFT) and the QM/MM calculation. It enables efficient massive parallel computing up to one hundred thousands processes. It supports the relativistic effect and offers the basis choice between the Gaussian basis and the plane-wave basis.
Software package to implement Behler-Parinello neural network potentials. Potentials can be trained from structure-energy/ interatomic forces/stress data, and molecular dynamics calculations using LAMMPS can also be performed using learned potentials. A prediction uncertainty measure can also be calculated simultaneously.
Library for calculating Pfaffian (square root of determinant), which is defined for skew-symmetric matrices. Algorithms are implemented in several languages (Fortran, Python, Matlab, Mathematica) and users can choose favorite one. Interfaces for C are also provided.
Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform written in Python. Users can perform mean-field and post-mean-field methods with standard Gaussian basis functions. This package also provides several interfaces to other software such as BLOCK and Libxc.
Python/C++ based software package that employs deep learning techniques for construction of interatomic potentials. It implements the Deep Potential, which defines atomic environment descriptors with respect to a local reference frame. The output of many first-principles and molecular dynamics applications can be used as training data, and the trained potentials can be used for molecular dynamics calculations using LAMMPS and path integral molecular dynamics calculations using i-PI.
Kω implements large-scale parallel computing of the shifted Krylov subspace method. Using Kω, dynamical correlation functions can be efficiently calculated. This application includes a mini-application for calculating dynamical correlation functions of quantum lattice models such as the Hubbard model, the Kondo model, and the Heisenberg model in combination with the quantum lattice solver of quantum many-body problems, HΦ.
An electronic state solver distributed with GAMESS, the quantum chemical (QM) calculation software. Combining energy density analysis and Divide-and-Conquer (DC) method, accurate QM calculation with electronic correlation is solved in a short time. Highly accurate QM calculations for many-atom/nano-scale material can be solved when run on a high performance super computer.
An open-source application for quantum chemical calculation. This package implements various methods for quantum chemical calculation such as Hartree-Fock approximation, density functional theory, coupled-cluster method, and CI (configuration interaction) method. The package is written in C++, and provides API for Python, by which users can perform for preparation of setting and execution of calculation.
A collection of software tools for molecular dynamics calculations. Various interatomic potentials and tight binding models are implemented, and numerous external applications can be invoked. It also supports training and evaluation of GAP (Gaussian Approximation Potential), which is a form of machine learning potential.
An open-source application for molecular simulations. This application supports various methods such as classical and ab initio molecular dynamics, path integral simulations, replica exchange simulations, metadynamics, string method, surface hopping dynamics, QM/MM simulations, and so on. A hierarchical parallelization between molecular structures (replicas) and force fields (adiabatic potentials) enables fast and efficient computation.