NetKet

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

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.

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SHRY

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

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.

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Bilbao Crystallographic Server

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

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.

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cdview

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

An open-source application for visualization of many-particle systems. With simple operation by graphical user interface (GUI) or by command line, this application can visualize particle positions obtained from molecular dynamics simulation as well as three-dimensional scalar quantities such as potential energies. It supports various display options on kinds and shapes of particles, and can also visualize bond formation between particles.

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Open Source MPS

  • Level of openness 2 ★★☆
  • Document quality 2 ★★☆

An open-source application for simulation of one-dimensional interacting electron models based on a tensor product wavefunction method. This application supports not only electronic models but also spin and bosonic models, and can evaluate various physical quantities for ground states and low-lying excited states. This application also supports time evolution, and can treat models with long-range interactions.

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EDlib

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

EDlib is an app for performing finite-temperature exact diagonalizations for quantum many-body systems. EDlib is written in C++ and it is possible to obtain finite-temperature properties such as the one-body Green’s function in the Hubbard model and the Anderson model.

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RuNNer

  • Level of openness 1 ★☆☆
  • Document quality 2 ★★☆

FORTRAN-based software package developed by the Behler Group for implementing Behler-Parinello neural network potentials. Potentials can be constructed, evaluated, and used for molecular dynamics simulations using LAMMPS. The newest generation of neural network potentials that take into account long-range electrostatic interactions are implemented.

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DMRG++

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

An open-source application for simulation based on the density-matrix renormalization group (DMRG). This application can perform high-speed calculation of low-dimensional quantum systems with high accuracy. It implements generic programming techniques in the C++ language, and can easily extend simulation to new models and geometries. It is developed putting emphasis on user-friendly interfaces and low dependences on environments.

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Harlem

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

An open-source multi-purpose application for modeling and visualizing molecules (biomolecules, in particular). This application has been developed for multi-scale molecular simulation, and also provides a simple GUI for AMBER and Gaussian. It also implements exchange of protein residues and the Pathways model for the electron transfer in proteins. It calls rasmol for visualization of atoms and molecules.

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SPINPACK

  • Level of openness 3 ★★★
  • Document quality 2 ★★☆

A free software library for numerical diagonalization of quantum spin systems. Although the programs are based on TITPACK, they have been completely rewritten in C/C++ and several extensions have been added. It can handle, for example, the Heisenberg model, the Hubbard model, and the t-J model. This library supports dimension reduction of matrices exploiting symmetries, and it can run in parallel computing environments.

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