Open source library to record execution and communication time during specified regions in user’s program. C/C++ and Fortran API are provided. This can profile MPI & OpenMP hybrid parallel programs as well as serial ones.
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.
An application for three-dimensional visualization with the ray tracing method. This application can visualize arbitrary positions and shapes of objects such as spheres and cubes. It can visualize three-dimensional data obtained from computational fluid dynamics etc. by volume rendering. It can also be used for simple three-dimensional graphical simulator with macro functions.
A python package for the tight-binding method. PythTB supports tight-binding calculations of electronic structures and Berry phase in various kinds of systems. Users can use ab initio parameters obtained by Wannier90.
peps-torch is a python library for calculation of quantum many-body problems on two dimensional lattices. Variational principles calculation is used with an infinite PEPS (iPEPS) as the trial wave function. Therefore, the ground state is obtained in the form of the element tensor of the iPEPS. The energy of the trial state is estimated by the corner transfer matrix method (CTM), and its gradient with respect to the element tensor is computed through automatic differentiation provided by pytorch. Functions/classes for exploiting the system’s symmetry are provided for reducing the computational cost if possible. While general models and lattices are not supported, many examples of stand-alone codes would make it relatively easy for users to write their own codes to suit their needs. pytorch is required.
PAICS is a program of quantum chemical calculation. In this program, fragment molecular orbital (FMO) method is adopted, by which large molecules including biomolecular systems can be treated with several quantum chemical approaches including HF and MP2 methods. At the same time, PaicsView has been developed, which is a supporting program for making input files and analyzing calculation results.
A python library for materials analysis. Flexible classes for representation of materials are prepared, and data for crystal structures and various material properties can be handled efficiently. This application can performs analysis of phase diagrams, Pourbaix diagrams, diffusion analyses etc. as well as electronic structure analyses such as density of states and band structures. This software is being actively developed keeping close relation with Materials Project.
A python library for pre- and post-processing of first-principles electronic structure calculations. As a pre-processing tool, it can automatically generate k-point pathways for first-principles calculations of band structures based on the crystal symmetry. It can also post-process first-principles calculation results to generate band structure and density of states plots with atomic species and orbital contributions, or visualize spin textures and Fermi surfaces. It also provides a functionality for band unfolding.
An application for visualization of biopolymers. This application can visualize biopolymers by using its original command line and graphical user interface, more than 600 settings for visualization, and more than 20 visualization schemes. This application also supports more than 30 file formats such as PDB and multi-SDF, and can utilize sophisticated visualization methods such as the ray tracing.
Software tool for constructing interatomic potentials based on nonlinear atomic cluster expansion. It requires the user to either prepare a fitting dataset based on pandas and ASE, or it can automatically extract data from VASP calculation results. The obtained potentials can be used for molecular dynamics simulations using LAMMPS, and it also provides the capability to calculate extrapolation grades for on-the-fly active learning.