ALPSCore/CT-HYB

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

An open-source impurity solver based on the quantum Monte Carlo method. Thermal equilibrium states of interacting impurity systems, such as the impurity Anderson model, can be evaluated by the continuous-time hybridization-expansion quantum Monte Carlo method. It can be used as a solver of effective impurity models derived from the dynamical mean-field theory (DMFT) and can deal with multi-orbital models. This package supports parallel computation by MPI and is developed based on the ALPSCore library.

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TRIQS/CTHYB

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

An open-source solver for the impurity problem based on the continuous-time quantum Monte Carlo method. Imaginary-time Green’s functions of the impurity Anderson model and the effective impurity model in the dynamical mean-field approximation can be calculated with high speed by using an efficient Monte Carlo algorithm. The main programs are written by C++, and can be called from Python scripts.

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TRIQS/DFT tools

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

An interface tool for combining first-principles calculation based on density functional theory (DFT) and TRIQS, the application for dynamical mean-field theory (DMFT). By combining Wien2k and TRIQS, self-consistent DFT+DMFT calculation can be realized by this tool. One-shot DFT+DMFT calculation using band structures obtained by other first-principles applications is also possible.

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ComDMFT

  • Level of openness 3 ★★★
  • Document quality 1 ★☆☆

ComDMFT is a massively parallel computational package to study the electronic structure of correlated-electron systems. Users can perform a parameter-free method based on ab initio linearized quasiparticle self-consistent GW (LQSGW) and dynamical mean field theory (DMFT).

 

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SpM

  • Level of openness 3 ★★★
  • Document quality 1 ★☆☆

A sparse-modeling tool for computing the spectral function from the imaginary-time Green function. It removes statistical errors in quantum Monte Carlo data, and performs a stable analytical continuation. The obtained spectral function fulfills the non-negativity and the sum rule. The computation is fast and free from tuning parameters.

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