The *Munich Quantum Toolkit (MQT)* is a comprehensive collection of software tools developed by the Chair for Design Automation at the Technical University of Munich. These tools aim to address various aspects of quantum computing, including classical simulation, compilation, verification, and error correction. The MQT leverages design automation expertise to provide efficient and user-friendly solutions for end users, engineers, and physicists across the entire quantum software stack. Key features include: 1. **Classical Simulation**: Tools like DDSIM use decision diagrams to simulate quantum circuits, supporting strong and weak simulation, approximation techniques, noise-aware simulation, and more. 2. **Compilation**: The QMAP tool helps map quantum circuits to specific quantum devices, minimizing the overhead of additional gates and ensuring compatibility with device constraints. 3. **Verification**: The QCEC tool offers efficient methods for verifying the equivalence of quantum circuits, leveraging the reversibility of quantum operations to simplify the verification process. 4. **Error Correction**: The MQT includes tools for quantum error correction, supporting physical design, and other advanced features. 5. **Benchmarking**: MQTT Bench provides over 70,000 benchmarks to evaluate the performance of quantum software tools, ensuring comparability and reproducibility. All tools are available as open-source implementations on GitHub, with Python bindings and integration with IBM’s Qiskit. The MQT aims to support researchers, developers, and practitioners in the near-, middle-, and far-term future of quantum computing by providing a robust suite of tools and methods.The *Munich Quantum Toolkit (MQT)* is a comprehensive collection of software tools developed by the Chair for Design Automation at the Technical University of Munich. These tools aim to address various aspects of quantum computing, including classical simulation, compilation, verification, and error correction. The MQT leverages design automation expertise to provide efficient and user-friendly solutions for end users, engineers, and physicists across the entire quantum software stack. Key features include: 1. **Classical Simulation**: Tools like DDSIM use decision diagrams to simulate quantum circuits, supporting strong and weak simulation, approximation techniques, noise-aware simulation, and more. 2. **Compilation**: The QMAP tool helps map quantum circuits to specific quantum devices, minimizing the overhead of additional gates and ensuring compatibility with device constraints. 3. **Verification**: The QCEC tool offers efficient methods for verifying the equivalence of quantum circuits, leveraging the reversibility of quantum operations to simplify the verification process. 4. **Error Correction**: The MQT includes tools for quantum error correction, supporting physical design, and other advanced features. 5. **Benchmarking**: MQTT Bench provides over 70,000 benchmarks to evaluate the performance of quantum software tools, ensuring comparability and reproducibility. All tools are available as open-source implementations on GitHub, with Python bindings and integration with IBM’s Qiskit. The MQT aims to support researchers, developers, and practitioners in the near-, middle-, and far-term future of quantum computing by providing a robust suite of tools and methods.