Transpilers

Integrate ZX-Calculus optimization into Qiskit workflows. This transpiler pass uses PyZX to simplify quantum circuits, reducing depth and gate count.

Manage quantum jobs across diverse hardware and software platforms. This Python SDK provides a platform-agnostic runtime, configurable transpilation, and modular tools for the full job lifecycle.

Perform high-speed analysis, synthesis, compilation, and optimization of quantum circuits using a scalable C++17 library designed for performance and flexibility.

Implement quantum programs in Python with intuitive syntax. Translate code for execution on classical simulators or actual quantum hardware. Open-source framework.

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

Software platform for the development and execution of gate-level quantum computation, providing state-of-the-art performance in circuit compilation. The toolset is designed to aid platform-agnostic software and extract the most out of the available NISQ devices of today.

Write, manipulate, and optimize quantum circuits in Python. Run them on quantum hardware and simulators, leveraging hardware-specific details crucial for noisy intermediate-scale devices.

Build, refine, and execute quantum workloads at scale. This open-source toolkit is the highest-performing SDK for building and transpiling circuits, offering simplified workflows and powerful tools.