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A quantum simulator based on decision diagrams written in C++

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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.

Documentation

Key Features

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.

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

Contributors to munich-quantum-toolkit/ddsim

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:

Sponsor the MQT

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] L. Burgholzer, A. Ploier, and R. Wille. Exploiting Arbitrary Paths for the Simulation of Quantum Circuits with Decision Diagrams. In Design, Automation and Test in Europe (DATE), 2022.

[6] T. Grurl, J. Fuß, and R. Wille. Noise-aware Quantum Circuit Simulation with Decision Diagrams. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022.


Acknowledgements

The Munich Quantum Toolkit has been supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 101001318), the Bavarian State Ministry for Science and Arts through the Distinguished Professorship Program, as well as the Munich Quantum Valley, which is supported by the Bavarian state government with funds from the Hightech Agenda Bayern Plus.

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