QuSpin

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

QuSpin is a python package for performing exact diagonalization and real- or imaginary-time evolution for quantum many-body systems. Using QuSpin, for example, it is possible to study the many-body localization and the quantum quenches in the Heisenberg chain. Moreover, QuSpin specifies the symmetries in the systems such as the total magnetization, the parity, the spin inversion, the translation symmetry, and their combinations.

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DiracQ

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

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.

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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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OpenFermion

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

Open-source software for quantum computing in quantum chemistry. OpenFermion can map the ab-initio Hamiltonian of an target molecular or material in second quantization to that in qubits. Parameters of the Hamiltonian is estimated by using other software for first-principles calculations. OpenFermion also provides users plugins to support integration with apps for quantum circuits and quantum simulators.

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Mm2cML

  • Level of openness 0 ☆☆☆
  • Document quality 2 ★★☆

Mm2cML is a web application that structure files can be generated from molecular model images. By carrying out three-dimensional reconstruction using OpenMVG and OpenMVS from molecular model images photographed by smartphones or digital cameras, and arranging atoms on the basis of them, users can obtain structure files (CML format) usable for molecular simulation. The simulation can be carried out on the basis of the structure examined using the molecular model in the real world.

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AMULET

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

AMULET is a collection of tools for a first principles calculation of physical properties of strongly correlated materials. It is based on density functional theory (DFT) combined with dynamical mean-field theory (DMFT). Users can calculate physical properties of chemically disordered compounds and alloys within CPA+DMFT formalism.

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Blueqat

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

Open-source Python code for simulation of gate-type quantum computers. Blueqat can call Qiskit, a quantum computing development tool, to run IBM Q, a gate-type quantum computer.

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TeNeS

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

A solver program for two dimensional quantum lattice model based on a projected entangled pair state wavefunction and the corner transfer matrix renormalization group method.
This works on a massively parallel machine because tensor operations are OpenMP/MPI parallelized.

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abICS

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

Software framework for training a machine learning model to reproduce first-principles energies and then using the model to perform configurational sampling in disordered systems. It has been developed with an emphasis on multi-component solid-state systems such as metal and oxide alloys. At present, Quantum Espresso, VASP and OpenMX can be used as first-principles energy calculators, and aenet can be used to construct neural network potentials.

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ALPSCore

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

Open-source software for building computational physics applications. Common C++ auxiliary modules required for various methods in computational physics such as the quantum Monte Carlo method are prepared. This software helps to build reusable codes and to reduce development time for complex computational science applications. It also supports parallel programming based on MPI or OpenMP.

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