MQT DDSIM - A quantum circuit simulator based on decision diagrams written in C++

A tool for classical quantum circuit simulation developed as part of the Munich Quantum Toolkit (MQT). It builds upon MQT Core, which forms the backbone of the MQT.

Key Features

• Decision-diagram–based circuit simulation: Circuit Simulator—strong (statevector) and weak (sampling), incl. mid‑circuit measurements and resets; Qiskit backends (qasm_simulator and statevector_simulator). Quickstart • API
• Unitary simulation: Unitary Simulator with an optional alternative recursive construction for improved intermediate compactness.
• Hybrid Schrödinger–Feynman simulation: Hybrid simulator trading memory for runtime with DD and amplitude modes plus multithreading; also available as a statevector backend.
• Simulation Path Framework: Path-based simulation with strategies sequential, pairwise_recursive, bracket, and alternating.
• Noise-aware simulation: Stochastic and deterministic noise (amplitude damping, depolarization, phase flip; density-matrix mode) for global decoherence and gate errors.

If you have any questions, feel free to create a discussion or an issue on GitHub.

Contributors and Supporters

The Munich Quantum Toolkit (MQT) is developed by the Chair for Design Automation at the Technical University of Munich and supported by MQSC. Among others, it is part of the Munich Quantum Software Stack (MQSS) ecosystem, which is being developed as part of the Munich Quantum Valley (MQV) initiative.

Thank you to all the contributors who have helped make MQT DDSIM a reality!

The MQT will remain free, open-source, and permissively licensed—now and in the future. We are firmly committed to keeping it open and actively maintained for the quantum computing community.

To support this endeavor, please consider:

• Starring and sharing our repositories: https://github.com/munich-quantum-toolkit
• Contributing code, documentation, tests, or examples via issues and pull requests
• Citing the MQT in your publications (see Cite This)
• Citing our research in your publications (see References)
• Using the MQT in research and teaching, and sharing feedback and use cases
• Sponsoring us on GitHub: https://github.com/sponsors/munich-quantum-toolkit

Getting Started

MQT DDSIM bundled with the provider and backends for Qiskit is available via PyPI.

uv pip install mqt.ddsim

The following code gives an example on the usage:

from qiskit import QuantumCircuit
from mqt import ddsim

circ = QuantumCircuit(3)
circ.h(0)
circ.cx(0, 1)
circ.cx(0, 2)

print(circ.draw(fold=-1))

backend = ddsim.DDSIMProvider().get_backend("qasm_simulator")

job = backend.run(circ, shots=10000)
counts = job.result().get_counts(circ)
print(counts)

Detailed documentation and examples are available at ReadTheDocs.

System Requirements and Building

Building the project requires a C++ compiler with support for C++20 and CMake 3.24 or newer. For details on how to build the project, please refer to the documentation. Building (and running) is continuously tested under Linux, macOS, and Windows using the latest available system versions for GitHub Actions. MQT DDSIM is compatible with all officially supported Python versions.

Cite This

Please cite the work that best fits your use case.

MQT DDSIM (the tool)

When citing the software itself or results produced with it, cite the original DD simulation paper:

@article{zulehner2019advanced,
  title        = {Advanced Simulation of Quantum Computations},
  author       = {Zulehner, Alwin and Wille, Robert},
  year         = 2019,
  journal      = {tcad},
  volume       = 38,
  number       = 5,
  pages        = {848--859},
  doi          = {10.1109/TCAD.2018.2834427}
}

The Munich Quantum Toolkit (the project)

When discussing the overall MQT project or its ecosystem, cite the MQT Handbook:

@inproceedings{mqt,
  title        = {The {{MQT}} Handbook: {{A}} Summary of Design Automation Tools and Software for Quantum Computing},
  shorttitle   = {{The MQT Handbook}},
  author       = {Wille, Robert and Berent, Lucas and Forster, Tobias and Kunasaikaran, Jagatheesan and Mato, Kevin and Peham, Tom and Quetschlich, Nils and Rovara, Damian and Sander, Aaron and Schmid, Ludwig and Schoenberger, Daniel and Stade, Yannick and Burgholzer, Lukas},
  year         = 2024,
  booktitle    = {IEEE International Conference on Quantum Software (QSW)},
  doi          = {10.1109/QSW62656.2024.00013},
  eprint       = {2405.17543},
  eprinttype   = {arxiv},
  addendum     = {A live version of this document is available at \url{https://mqt.readthedocs.io}}
}

Peer-Reviewed Research

When citing the underlying methods and research, please reference the most relevant peer-reviewed publications from the list below:

[1] A. Zulehner and R. Wille. Advanced Simulation of Quantum Computations. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2019.

[2] S. Hillmich, I. L. Markov, and R. Wille. Just Like the Real Thing: Fast Weak Simulation of Quantum Computation. In Design Automation Conference (DAC), 2020.

[3] S. Hillmich, R. Kueng, I. L. Markov, and R. Wille. As Accurate as Needed, as Efficient as Possible: Approximations in DD-based Quantum Circuit Simulation. In Design, Automation and Test in Europe (DATE), 2021.

[4] L. Burgholzer, H. Bauer, and R. Wille. Hybrid Schrödinger–Feynman Simulation of Quantum Circuits with Decision Diagrams. In IEEE International Conference on Quantum Computing and Engineering (QCE), 2021.

[[5]](https://www.cda.cit.tum.de/files/eda/2022_date_exploiting_