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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TeNPy

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

A Python library for simulating strongly correlated quantum systems using tensor networks. The goal is to make the algorithms readable and easy to use for beginners, and also powerful and fast for experts. Simple sample code and toy code to illustrate TEBD and DMRG are also provided.

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DSQSS

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

DSQSS is an application program for solving quantum many body problems in a discrete set (typically a lattice). It carries out quantum Monte Carlo simulations that sample from the Feynman path integral using the worm update. It can handle any lattice geometry and interaction.

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GENESIS

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

An open-source application for molecular dynamics simulation of biomolecules. This application is optimized for massive parallel computing environments such as the K-computer, and can perform high-speed molecular dynamical simulation of proteins and biomolecules. This application supports both all atoms calculation and coarse-grained model calculation, and can treat extended ensemble such as a replica exchange method. This code is released under GPL license.

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Allegro

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

Open source software for constructing the Allegro potential model based on E(3)-equivariant graph neural networks and using the potential model for molecular dynamics simulations. The code depends on NequIP and can be run in a similar manner. Allegro scales better than NequIP since it doesn’t rely on message passing and the architecture is strictly local with respect to atom-wise environments.

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FMO in GAMESS

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

The fragment molecular orbital (FMO) method can efficiently do quantum-mechanical calculations of large molecular systems by splitting the whole system into small fragments. The FMO program is distributed within quantum-chemical program suite GAMESS-US. FMO can provide various information regarding the structure and function of biopolymers, such as the interaction between a protein and a ligand.

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TensorNetwork

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

An open source library for implementing tensor networks. It is developed based on TensorFlow and is designed to be easily used by experts in the field of machine learning as well as in the field of physics. In addition to TensorFlow, it includes wrappers for JAX, PyTorch, and Numpy.

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ATAT

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

A set of tools for alloy theory analysis in combination with first-principles calculation packages. Free energy and thermodynamic phase diagrams of alloy systems are calculated by combining the cluster expansion method with Monte Carlo simulations. Interfaces with major first-principles code including Quantum Espresso, VASP, and ABINIT are provided.

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KOBEPACK

  • Level of openness 3 ★★★
  • Document quality 0 ☆☆☆

An open-source program package for numerical diagonalization based on the Lanczos method, specialized for spin chains with unit spin magnitude, S=1. This package, which uses another open-source program package, TITPACK, calculates eigenenergies and eigenvectors of ground states and low-lying excited states of spin chains with finite length. By the subspace partitioning method, both memory and cpu-time requirements are considerably reduced.

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pacemaker

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

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.

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