Quantum Algorithms Tools

An open-source platform integrating QPUs, GPUs, and CPUs for hybrid quantum-classical computing. Enables QPU-agnostic development and offers GPU-accelerated simulations.

Simulate large, noisy, and parametric quantum circuits rapidly using a parallelized C++/Python library with GPU acceleration and built-in noise models.

Extensible, Efficient Quantum Algorithm Design For Humans.

Build and train quantum neural networks with a cloud-integrated platform. Offers easy-to-use APIs, comprehensive tutorials, toolkits for chemistry/optimization, and large-scale simulation.

QCL is a high-level, architecture-independent quantum programming language with syntax like C/Pascal, enabling full algorithm implementation and simulation.

Implement Variational Quantum Eigensolver on photonic hardware. Compile quantum circuits for Perceval processors and utilize quantum chemistry tools.

The Munich Quantum Toolkit (MQT) is a collection of software tools for quantum computing that explicitly utilizes this design automation expertise.

MQT DDVis - An installation-free web-tool which visualizes quantum decision diagrams and allows to explore their behavior when used in design tasks such as simulation, synthesis, or verification.

The package also aims for a more general way of defining control problems with QuTiP and makes switching between the four control algorithms (GOAT, JOPT, and GRAPE and CRAB implemented in qutip-qtrl) very easy.

Develop, differentiate, and optimize quantum algorithms using abstract data structures. Execute on diverse simulators and hardware backends for variational quantum computation.