Qulacs

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

C ++ / Python library for simulation of quantum computer. Users can perform simulations of quantum circuits constructed from variational quantum circuits and noisy quantum gates for the development of NISQ devices. It also supports OpenMP and GPU parallelization.

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QS3

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

An exact diagonalization package for efficiently solving quantum spin 1/2 lattice models in almost fully spin-polarized sectors. QS3 can treat such systems with quite large system sizes, over 1000 sites. It supports calculations of wavenumber-dependence of energy-dispersion and dynamical spin structure factor.

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TurboGenius

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

Python wrapper to manage jobs for the ab initio Monte Carlo package TurboRVB. By combining with a workflow management application, TurboWorkflows,  users can perform high-throughput calculations based on TurboRVB.

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FDMNES

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

An application for first-principles calculation based on density functional theory (DFT) optimized for X-ray spectroscopy analysis. Theoretical prediction and data fitting for X-ray spectroscopy such as XANES(X-ray absorption fine structure), XMCD(X-ray magnetic circular dichroism), RXD(resonant X-ray diffraction) can be preformes. This application employs a fully relativistic LSDA calculation based on the finite element method, and also supports the LDA+U method and the TD-DFT calculation.

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CONQUEST

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

CONQUEST is a linear-scaling DFT (Density Functional Theory) code based on the density matrix minimization method. Since its computational cost, for both memory and computational costs, is only proportional to the number of atoms N of the target systems, the code can employ structure optimization or molecular dynamics on very large-scale systems, including more than hundreds of thousands of atoms. It also has high parallel efficiency and is suitable for massively parallel calculations.

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ParaView

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

An open-source application for analysis and visualization of two- and three-dimensional data. The function of this application can be used not only by interactive operation with three-dimensional display, but also by batch processing. This application supports various environments such as Windows, Mac, and Linux from a desktop PC to a supercomputer performing large scale parallel computation.

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wxMacMolPlt

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

An open-source application for visualization developed for input and output of GAMESS. This application supports various types of input formats such as GAMESS, XYZ, MolDel, pdb, and CML as well as input by GUI and the Z-matrix format. It can visualize molecular orbitals, electron densities, electrostatic potentials, and normal modes, and can output results into various formats.

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Cirq

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

A Python framework for easy creation, manipulation and optimization of quantum algorithms for NISQ (Noisy Intermediate Scale Quantum Computer). A simulator for the quantum processor in the Xmon architecture provided by Google has also been supported.

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PyProcar

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

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.

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DiffPy

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

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.

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