BerkeleyGW is an open-source program package to calculate quasi-particle spectrum and optical responses from mean-field result by using GW approximation and Bethe-Salpeter equation. This is compatible with output files of many commonly used DFT codes such as Quantum ESPRESSO.
An open-source application for first-principles calculation based on pseudopotential and wavelet basis. Electronic state calculation of massive systems is performed with high accuracy and high efficiency by using adaptive mesh. Parallel computing by MPI, OpenMP, and GPU is also supported.
A tool for performing Bader analysis of assigning electron density of molecules and solids to individual atoms. Binaries for Linux and Mac OS X, as well as source code is provided under the GPL. The code is written in fortran90, and can handle charge density data in VASP CHGCAR and Gaussian Cube formats.
Web server that offers various crystallographic tools free of charge. The server offers over 70 tools/utilities related to space group, magnetic space group, representation theory, scattering theory, etc. The tools are accessed through a web interface.
An open-source application for quantum chemical calculation based on the density-matrix renormalization group (DMRG). For systems with a number of atomic orbitals, low-lying energy eigenvalues can be calculated in high accuracy of order of 1kcal/mol. This application is suitable especially to calculation of multi-orbital systems with one-dimensional topology such as chain-like or circular-like configuration of orbits.
An application for calculating transport coefficients based on the Boltzman equation. Within the relaxation time approximation, transport coefficients such as the Hall coefficient and the Seebeck coefficient can be evaluated from the output of the first principles calculation applications (Wien2k, ABINIT, SIESTA, quantum ESPRESSO, VASP). If users can measure relaxation time experimentally, electric conductivity can also be evaluated.
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.