MQT Core - The Backbone of the Munich Quantum Toolkit (MQT)

MQT Core is a collection of open-source C++20 and Python libraries for quantum computing. Its MQT Compiler Collection is built on MLIR and LLVM and connects structured quantum-classical programs to optimization, hardware mapping, and execution. Its libraries form the backbone of the Munich Quantum Toolkit (MQT).

MQT Core 4 is a major architectural release: the compiler's program representations replace the classic circuit APIs. Start with the v4 release overview and v3-to-v4 upgrade guide when migrating an existing application. The low-level DD and QDMI libraries remain available.

Key Features

• MQT Compiler Collection: Generate and optimize structured quantum/classical programs, map them to devices, synthesize native gates, and exchange programs through OpenQASM, Qiskit, QIR, and jeff.
• Decision diagrams: Represent quantum states and operations, simulate programs, and analyze their behavior through C++ and Python.
• QIR execution: Execute supported QIR Base and Adaptive Profile programs with the DD runtime.
• QDMI: Discover devices, query capabilities, compile programs, and submit jobs. Use bundled DDSIM for execution and superconducting hardware models for compilation.
• SDK and HPC integration: connect devices through Qiskit, PennyLane, and Slurm.
• Structured benchmarks: Generate configurable quantum programs, query analytic references, and evaluate sampled results.

Getting Started

Install mqt.core in a Python 3.11 or newer virtual environment:

uv pip install mqt.core

Estimate the phase 3/8 with eight bits of precision using iterative quantum phase estimation (QPE). This uses two qubits and measurement feedback. Compile for the bundled DDSIM device, then submit the compiled program:

from fractions import Fraction

from mqt.core.bench import qpe
from mqt.core.mlir import compile_program, submit_program
from mqt.core.qdmi.driver import open_device

benchmark = qpe.QPE(qpe.Options(precision=8, phase=Fraction(3, 8), method=qpe.Method.ITERATIVE))
program = benchmark.generate()
device = open_device("mqt.ddsim.default")
compiled = compile_program(program, target=device)
job = submit_program(compiled, target=device, num_shots=1024)
job.wait()

counts = job.get_counts()
outcome = max(counts, key=lambda bits: counts[bits])
phase = Fraction(int(outcome, 2), 2**benchmark.output.width)
assert phase == benchmark.options.phase
assert benchmark.evaluate(counts).total_variation_distance < 1e-12
print(f"Counts: {counts}")
print(f"Estimated phase: {phase}")

Counts: {'01100000': 1024}
Estimated phase: 3/8

The QPE walkthrough compares standard and iterative QPE and evaluates a phase that cannot be represented exactly with eight bits. This phase-gate benchmark illustrates the phase-estimation step used in algorithms such as Shor's.

Further Documentation

• Install and build MQT Core.
• Compile and execute programs.
• Browse the Python API and C++ entry point.

Development

Source builds require a C++20 compiler and CMake 3.28 or newer. Building the compiler collection also requires LLVM/MLIR 23.1 or newer. Prebuilt Python wheels include the compiler and simulator. Graphviz is optional for exporting DD visualizations.

See the contribution guide for development setup and checks. For questions and suggestions, open a discussion or an issue.

Contributors and Supporters

MQT Core is developed by MQSC and the Chair for Design Automation at the Technical University of Munich. 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 Core 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

Cite This

Please cite the work that best fits your use case.

MQT Core (the tool)

When citing the software itself or results produced with it, cite the MQT Core paper:

@article{burgholzer2025MQTCore,
  title        = {{{MQT Core}}: {{The}} Backbone of the {{Munich Quantum Toolkit (MQT)}}},
  author       = {Burgholzer, Lukas and Stade, Yannick and Peham, Tom and Wille, Robert},
  year         = 2025,
  journal      = {Journal of Open Source Software},
  publisher    = {The Open Journal},
  volume       = 10,
  number       = 108,
  pages        = 7478,
  doi          = {10.21105/joss.07478},
  url          = {https://doi.org/10.21105/joss.07478}
}

The MQT Compiler Collection

When citing the compilation framework built on MLIR, cite the MQT Compiler Collection paper:

@article{MQTCompilerCollection2026,
  title        = {The {{MQT Compiler Collection}}: {{A}} Blueprint for a Future-Proof Quantum-Classical Compilation Framework},
  author       = {Burgholzer, Lukas and Haag, Daniel and Stade, Yannick and Rovara, Damian and Hopf, Patrick and Wille, Robert},
  year         = {2026},
  booktitle    = {Design, Automation and Test in Europe},
  doi          = {10.23919/DATE69613.2026.11539504},
  eprint       = {2604.08674},
  eprinttype   = {arxiv},
}

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}}
}

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.