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.
QMCPACK is a modern high-performance open-source Quantum Monte Carlo (QMC) simulation code. Its main applications are electronic structure calculations of molecular, quasi-2D and solid-state systems. Variational Monte Carlo (VMC), diffusion Monte Carlo (DMC), orbital space auxiliary field QMC (AFQMC) and a number of other advanced QMC algorithms are implemented.
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.
QuCumber is an open-source Python package that implements neural-network quantum state reconstruction of many-body wavefunctions from measurement data such as magnetic spin projections, orbital occupation number. Given a training dataset of measurements, QuCumber discovers the most likely quantum state compatible with the measurements by finding the optimal set of parameters of a restricted Boltzmann machine (RBM).
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.
RESPACK is a first-principles calculation software for evaluating the interaction parameters of materials. It is able to calculate the maximally localized Wannier functions, the RPA response functions, and frequency-dependent electronic interaction parameters. RESPACK receives its input data from a band calculation using norm-conserving pseudopotentials with plane-wave basis sets. Utilities which convert a result of xTAPP or Quantum ESPRESSO to an input for RESPACK are prepared. The software has been used successfully for a wide range of materials such as metals, semiconductors, transition-metal compounds, and organic compounds. It supports OpenMP / MPI parallelization.
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.
An open-source application for simulation of low-dimensional interacting electron models based on density-matrix renormalization group (DMRG). For effective models of one-dimensional quantum systems and impurity systems, this application can treat not only physical quantities of ground states but also time evolution and finite-temperature physical quantities. The program is coded in C++, and can be called from MATLAB scripts.
Server for computing exact ground state of Ising model with random interacitons (Ising spin glasses). Users can specify the distributions of the interactions and the geometry of lattices. By inputting the informaiont of the model, users will receive the computational results by e-mail from the server.
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.