Fitting data to a scaling law of critical phenomena, we automatically estimate critical point and indices. Since Bayesian method is flexible, we can use all data in a critical region.
A support application for preparing input files of molecular dynamics calculation. This application supports manual input of atomic coordinates and bond informations, reading files of protain structure database, and editing data by graphical user interface. It also implements various functions such as addition of hydrogen atoms and composition of data. and can treat a large number of atoms using only a moderate memory cost.
MDACP (Molecular Dynamics code for Avogadro Challenge Project) is an efficient implementations of classical molecular dynamics (MD) method for the Lennard-Jones particle systems. MDACP Ver. 1.xx adopts flat-MPI and Ver. 2.xx adopts MPI+OpenMP hybrid parallelization.
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.
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.
Elastic is a set of python routines for calculation of elastic properties of crystals (elastic constants, equation of state, sound velocities, etc.). It is implemented as a extension to the Atomic Simulation Environment (ASE) system. There is a script providing interface to the library not requiring knowledge of python or ASE system.
NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and machine learning techniques. Users can perform machine learning algorithms to find the ground-state of many-body Hamiltonians such as supervised learning of a given state and optimization of neural network states by using the variational Monte Carlo method.
A python tool for generating symmetry-inequivalent supercell structures from a CIF file containing site occupancy information. SHRY can be used as a command-line tool as well as a module in a python script.
Open source Python package for data mining of materials. It can extract data from more than dozens of databases, perform preprocessing and visualization of extracted data. By combining machine-learning tools such as scikit-learn, users can build machine-learning models with descriptors created from the extracted data.
ALPS is a numerical simulation library for strongly correlated systems such as magnetic materials or correlated electrons. It contains typicalsolvers for strongly correlated systems: Monte Carlo methods, exact diagonalization, the density matrix renormalization group, etc. It can be used to calculate heat capacities, susceptibilities, magnetization processes in interacting spin systems, the density of states in strongly correlated electrons, etc. A highly efficient scheduler for parallel computing is another improvement.
※Related links are temporary changed due to the server maintenance for ALPS project.