An exact diagonalization package for efficiently solving quantum spin 1/2 lattice models in almost fully spin-polarized sectors. QS3 can treat such systems with quite large system sizes, over 1000 sites. It supports calculations of wavenumber-dependence of energy-dispersion and dynamical spin structure factor.
An open-source application for simulation based on the density-matrix renormalization group (DMRG). This application can perform high-speed calculation of low-dimensional quantum systems with high accuracy. It implements generic programming techniques in the C++ language, and can easily extend simulation to new models and geometries. It is developed putting emphasis on user-friendly interfaces and low dependences on environments.
A tool for performing quantum many-body simulations based on dynamical mean-field theory. In addition to predefined models, one can construct and solve an ab-initio tight-binding model by using wannier 90 or RESPACK. We provide a post-processing tool for computing physical quantities such as the density of state and the momentum resolved spectral function. DCore depends on external libraries such as TRIQS and ALPSCore.
An exact diagonalization package for a wide range of quantum lattice models (e.g. multi-orbital Hubbard model, Heisenberg model, Kondo lattice model). HΦ also supports the massively parallel computations. The Lanczos algorithm for obtaining the ground state and thermal pure quantum state method for finite-temperature calculations are implemented. In addition, dynamical Green’s functions can be calculated using Kω, which is a library of the shifted Krylov subspace method. It is possible to perform simulations for real-time evolution from ver. 3.0.
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.
A low-energy solver for a wide ranger of quantum lattice models (multi-orbital Hubbard model, Heisenberg model, Kondo-lattice model) by using variational Monte Carlo method. User can obtain high-accuracy wave functions for ground states of above models. Users flexibly choose the correlation factors in wavefunctions such as Gutzwiller, Jastrow, and doublon-holon binding factors and optimize more the ten thousand variational parameters. It is also possible to obtain the low-energy excited states by specifying the quantum number using the quantum number projection.
A python package for the tight-binding method. PythTB supports tight-binding calculations of electronic structures and Berry phase in various kinds of systems. Users can use ab initio parameters obtained by Wannier90.
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.
An open-source application for obtaining optimized many-body wavefunctions expressed by matrix product states (MPS). By using a second-generation density matrix renormalization group (DMRG) algorithm, many-body wave functions can be efficiently optimized. The quantum-chemical operators are represented by matrix product operators (MPOs), which provides flexibility to accommodate various symmetries and relativistic effects.
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).