QMCPACK

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

QMCPACK is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code. Its main applications are electronic structure calculations of molecular, quasi-2D and solid-state systems. Variational Monte Carlo (VMC), diffusion Monte Carlo (DMC), orbital space auxiliary field QMC (AFQMC) and a number of other advanced QMC algorithms are implemented.

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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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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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TB2J

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

A python package for automatic calculation of magnetic effective interactions between atoms (exchange and Dzyaloshinskii-Moriya interactions) from ab initio Hamiltonians based on Wannier functions and LCAO calculations. The package can postprocess Hamiltonians calculated using Wannier90, Siesta, and OpenMX. Input files for magnetic structure simulators such as Vampire can also be generated.

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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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Uni10

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

An open source C++ library designed for the development of tensor network algorithms. The goal of this library is to provide basic tensor operations with an easy-to-use interface, and it also provides a Network class that handles the graphical representation of networks. A wrapper for calling it from Python is also provided.

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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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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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Rokko

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

A unified wrapper library for sequential and parallel versions of eigenvalue solvers. Sequential versions of dense-matrix diagonalization (LAPACK), parallel versions of dense-matrix diagonalization (EigenExa, ELPA, ScaLAPACK, etc.), and sequential/parallel versions of sparse-matrix diagonalization (SLEPc, Trilinos/Anasazi, etc.) can be installed quickly, and can be called from user’s program easily. Physical quantities written by eigenvalues or eigenvectors can also be evaluated by both sequential and parallel computation.

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