MQT QMAP: Efficient Quantum Circuit Mapping
arXiv:2301.11935 · doi:10.1145/3569052.3578928
Abstract
Quantum computing is an emerging technology that has the potential to revolutionize fields such as cryptography, machine learning, optimization, and quantum simulation. However, a major challenge in the realization of quantum algorithms on actual machines is ensuring that the gates in a quantum circuit (i.e., corresponding operations) match the topology of a targeted architecture so that the circuit can be executed while, at the same time, the resulting costs (e.g., in terms of the number of additionally introduced gates, fidelity, etc.) are kept low. This is known as the quantum circuit mapping problem. This summary paper provides an overview of QMAP, an open-source tool that is part of the Munich Quantum Toolkit (MQT) and offers efficient, automated, and accessible methods for tackling this problem. To this end, the paper first briefly reviews the problem. Afterwards, it shows how QMAP can be used to efficiently map quantum circuits to quantum computing architectures from both a user's and a developer's perspective. QMAP is publicly available as open-source at https://github.com/cda-tum/qmap.
arXiv comment7 pages, 6 figures, invited paper for the International Symposium on Physical Design (ISPD '23)
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- Optimizing Gate Decomposition for High-Level Quantum Programming
- Towards Supporting QIR: Steps for Adopting the Quantum Intermediate Representation
- Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware
- On the Impact of Classical and Quantum Communication Networks Upon Modular Quantum Computing Architecture System Performance
- Improving Figures of Merit for Quantum Circuit Compilation
- The MQT Compiler Collection: A Blueprint for a Future-Proof Quantum-Classical Compilation Framework
- Routing-Aware Placement for Zoned Neutral Atom-based Quantum Computing
- Generating Compilers for Qubit Mapping and Routing