C ++ / Python library for simulation of quantum computer. Users can perform simulations of quantum circuits constructed from variational quantum circuits and noisy quantum gates for the development of NISQ devices. It also supports OpenMP and GPU parallelization.
LIQ𝑈𝑖⏐〉is a software design architecture for quantum computing. It includes a programming language designed for quantum algorithms. By using LIQ𝑈𝑖⏐〉, users can design quantum circuits and perform simulations such as quantum teleportation and quantum chemistry.
A Python framework for easy creation, manipulation and optimization of quantum algorithms for NISQ (Noisy Intermediate Scale Quantum Computer). A simulator for the quantum processor in the Xmon architecture provided by Google has also been supported.
An open-source application for dynamical simulation of open quantum systems. It supports a wide range of Hamiltonians such as quantum optics, ion traps, and superconducting circuits. The time evolution of quantum states is evaluated by a master equation. These calculation library can be called from Python via a user-friendly interface.
Open-source software for quantum computing in quantum chemistry. OpenFermion can map the ab-initio Hamiltonian of an target molecular or material in second quantization to that in qubits. Parameters of the Hamiltonian is estimated by using other software for first-principles calculations. OpenFermion also provides users plugins to support integration with apps for quantum circuits and quantum simulators.
Open-source Python code for simulation of gate-type quantum computers. Blueqat can call Qiskit, a quantum computing development tool, to run IBM Q, a gate-type quantum computer.
Python library for the design, simulation, and optimization of continuous-variable quantum optical circuits. It has high-level functions for solving problems including graph and network optimization, machine learning, and chemistry, and can perform training and optimization of quantum programs using the TensorFlow backend.
Ising model and QUBO heuristic optimization library. The core of the optimization is implemented in C++; it has a Python interface, therefore it can be easily written in Python.