An open-source application for first-principles calculation utilizing the DV-Xα method. It produces electronic structure for a wide rage of physical systems such as atoms, molecules and crystals. The DV-Xα method realizes high-speed computation for all-electron calculations, and makes it possible to evaluate various physical properties and electron transition probability (especially of core-electron excitation). Tools for supplying input data, and visualizing and post-processing output data are also released.
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.
A tool for performing quantum many-body simulations based on dynamical mean-field theory. In addition to predefined models, one can construct and solve an ab-initio tight-binding model by using wannier 90 or RESPACK. We provide a post-processing tool for computing physical quantities such as the density of state and the momentum resolved spectral function. DCore depends on external libraries such as TRIQS and ALPSCore.
DCA++ is a software framework to solve correlated electron problems with modern quantum cluster methods. This code provides a state of the art implementation of the dynamical cluster approximation (DCA) and its DCA+ extension. As the cluster solvers, DCA++ provides the continuous-time auxiliary field QMC (CT-AUX) , the continuous-time hybridization expansion (CT-HYB) restricted to single-site problems, the high temperature series expansion (HTS) and the exact diagonalization(ED).
An application for data analysis of X-ray absorption fine structure (XAFS). Experimental data of XAFS can be analyzed by various analysis methods. This application supports various analysis functions (high-speed Fourier analysis, fitting in a radial coordinate or k-space, data plotting, etc.) based on IFEFFIT, and includes useful graphical user interface (GUI).
DiracQ is a Mathematica nodebook for calculating commutation relations, which frequently appear in the quantum mechanics. DiracQ can treat canonical operators (canonical momentum and canonical position operators), Fermion operators, and Boson operators.
An application for quantum chemical calculation based on DFTB (Density Functional based Tight Binding). This application performs structure
optimization and molecular dynamics by the DFTB force field as well as ordinary energy calculation, and implements parallel computing by OpenMP. A tool for visualization of molecular orbitals and an extended versions supporting MPI parallel computation or electron transport calculation by the nonequilibrium Green’s function method are also
available.
DAMASK is a unified multi-physics crystal plasticity simulation package. The solution of continuum mechanical boundary value problems requires a constitutive response that connects deformation and stress at each material point. This problem is solved in DAMASK on the basis of crystal plasticity using a variety of constitutive models and homogenization approaches. However, treating mechanics in isolation is no longer sufficient to study emergent advanced high-strength materials. In these materials, deformation happens interrelated with displacive phase transformation, significant heating, and potential damage evolution. Therefore, DAMASK is capable of handling multi-physics problems. Following a modular approach, additional field equations are solved in a fully coupled way using a staggered approach.
An open-source application for atomic structure analysis from powder diffraction data. This application can calculate atomic coordinates, valence sums, and chemical bonds from diffraction data of crystals, nanostructures, and amorphous materials. It is written in Python, and realizes multi-functional fitting and flexible data analysis.
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.