Open-source Python code for simulation of gate-type quantum computers. Blueqat can call Qiskit, a quantum computing development tool, to run IBM Q, a gate-type quantum computer.
A solver program for two dimensional quantum lattice model based on a projected entangled pair state wavefunction and the corner transfer matrix renormalization group method.
This works on a massively parallel machine because tensor operations are OpenMP/MPI parallelized.
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.
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.
Ab initio quantum Monte Carlo solver for both molecular and bulk electronic systems. By using the geminal/Pfaffian wavefunction with the Jastrow correlator as the trial wavefunction, users can perform highly accurate variational calculations, structural optimizations and ab initio molecular dynamics for both classical and quantum nuclei.
A library collection for numerical calculation of interacting quantum systems. Modern programming techniques are used in this library to implement common tasks for solving quantum impurity problems in dynamic mean-field theory in a simple and efficient way. It is written in C++ and Python, and includes tutorials using Jupyter Notebook.
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.
Starrydata is an open database of experimental data from figures in published papers. Thermoelectric properties such as Seebeck coefficient, electrical resistivity and thermal conductivity are presented mainly on thermoelectric materials.
PHYSBO is a Python library for researchers mainly in the materials science field to perform fast and scalable Bayesian optimization based on COMBO (Common Bayesian Optimization). Users can search the candidate with the largest objective function value from candidates listed in advance by using machine learning prediction. PHYSBO can handle a larger amount of data compared with standard implementations such as scikit-learn.