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.

A fast molecular dynamics simulator for ferroelectrics. This simulator can execute molecular dynamics calculations quickly by dealing with dipole interaction efficiently. It can simulate the physical property of microscopic ferroelectric thin film of tens of nanometers, which is important in FeRAM(Ferroelectric Random Access Memory), controlling the shapes and effects of inactivated layers.

An open source application implementing path-integral Monte Carlo method based on Stochastic Green function method. Finite temperature calculation of extended Bose Hubbard model and Heisenberg model with finite field can be treated. JSON and YAML formats are adopted for data I/O.

H-wave is a Python package for performing unrestricted Hartree-Fock (UHF) calculations and random phase approximation (RPA) calculations for itinerant electron systems. H-wave supports UHF calculations both in real- and wavenumber-spaces. H-wave supports one-body and two-body interactions in the Wannier90 format as inputs for H-wave, and thus users can solve *ab initio* effective Hamiltonians derived from Wannier90/RESPACK calculations based on UHF and RPA methods.

CCCM is a high-order CCM (coupled cluster method) code for lattice spin systems. It is possible to obtain the ground state and its energy of quantum spin systems in two or three dimensions.

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.

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.

An open-source application for quantum chemical calculation based on the density-matrix renormalization group (DMRG). For systems with a number of atomic orbitals, low-lying energy eigenvalues can be calculated in high accuracy of order of 1kcal/mol. This application is suitable especially to calculation of multi-orbital systems with one-dimensional topology such as chain-like or circular-like configuration of orbits.

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.

BEEMs is a Bayesian optimization tool of Effective Models (BEEMs). In BEEMs, the quantum lattice model solver HΦ is used as a forward problem solver to compute the magnetisation curve based on the given Hamiltonian. The deviation between the obtained magnetisation curve and the target magnetisation curve is used as a cost function, and the Bayesian optimization library PHYSBO is used to propose the next candidate point of the Hamiltonian for searching the minimum cost function