2DMAT is a framework for applying a search algorithm to a direct problem solver to find the optimal solution. In version 1.0, for solving a direct problem, 2DMAT offers the wrapper of the solver for the total-reflection high-energy positron diffraction (TRHEPD) experiment. As algorithms, it offers the Nelder-Mead method, the grid search method, the Bayesian optimization method, and the replica exchange Monte Carlo method. Users can define original direct problem solvers or the search algorithms.
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.
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.
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.
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.
Payware for the ab-initio quantum chemical calculation. This application preforms high-speed electronic structure calculation by introducing the RI approximation, and evaluates not only ground states but also excited states by various methods such as full RPA, TDDFT, CIS(D), CC2, ADC(2). It can also be used for evaluation of spectra data of infrared(IR), visible(Vis)/ultraviolet(UV), Raman, and circular dichroism spectroscopy.
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.
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.
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.
An open-source numerical library for machine learning. Various functions related to deep learning are implemented. This package directly treats equations as such, and have useful routines such as matrix operation and auto partial derivative. Users can convert their codes into C language, and can compile it. High speed operation by GPGPU parallel calculation is supported. A number of tutorials are available.