Superconducting Toolkit (sctk)

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

An open-source application for evaluating superconducting gaps from resutls of the first-principles calculation by Quantum ESPRESSO. By calculating electron-phonon interaction and screened Coulomb interaction from the first-principles calculation, superconducting gaps can be obtained from the gap equation. Quasiparticle densities of states and ultrasonic attenuation rates can also be calculated.

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TAPIOCA

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

A tool of input-file preparation and visualization for xTAPP, an application of the first-principle calculation. By graphical user interface (GUI), this application helps xTAPP users for making input files, and visualizes results of wavefunctions, electron densities, and potential profiles into three-dimensional graphics from output files.

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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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TC++

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

TC++ is open-source software for ab initio calculations using the transcorrelated (TC) method. In TC++, users can take account of electron correlations in a Jastrow correlation factor based on the TC method. Electronic structures obtained by Quantum ESPRESSO can be used as an initial state of TC++.

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Tecplot

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

Payware for visualization of computational fluid dynamics and general numerical simulation. This application provides an integrated environment for two- and three- dimensional graph drawing, and supports interactive visualization of data with many options such as slices, contours, and stream traces. It also supports visualization of large-scale data and efficient comparison between many data sets.

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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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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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Tensordot

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

Automatic generation tool for codes of tensor contraction. This tool can automatically generate codes of an optimal computing sequence for construction of a single tensor from a tensor network composed of tensors. Netcon algorithm proposed by Pfeifer et al. is used, and it is possible to search optimal solution quickly. Generated codes are available in Numpy and mptensor in Python.

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TensorFlow

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

A numerical library for machine learning. Various functions on machine learning (including supervised learning and unsupervised learning) are implemented in this package. Complex network can be expressed in a simple form by using data flow graphs. Efficient CPU/GPGPU parallel computation is supported to realise efficient operation on large scale data.

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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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