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Kölle, Michael; Bintener, Tom; Zorn, Maximilian ORCID logoORCID: https://orcid.org/0009-0006-2750-7495; Stenzel, Gerhard; Sünkel, Leo; Gabor, Thomas ORCID logoORCID: https://orcid.org/0000-0003-2048-8667 und Linnhoff-Popien, Claudia ORCID logoORCID: https://orcid.org/0000-0001-6284-9286 (2025): Evaluating Mutation Techniques in Genetic Algorithm-Based Quantum Circuit Synthesis. GECCO 2025: Genetic and Evolutionary Computation Conference, Málaga, Spain, 14.- 18. Juli 2025. Ochoa, Gabriela und Filipic, Bogdan (Hrsg.): In: GECCO '25: Proceedings of the Genetic and Evolutionary Computation Conference, New York, NY, USA: Association for Computing Machinery. S. 907-915

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Abstract

Quantum computing leverages the unique properties of qubits and quantum parallelism to solve problems intractable for classical systems, offering unparalleled computational potential. However, optimization of quantum circuits remains critical, especially for noisy intermediate-scale quantum (NISQ) devices with limited qubits and high error rates. Genetic algorithms (GAs) provide a promising approach for efficient quantum circuit synthesis by automating optimization tasks. This work examines the impact of various mutation strategies within a GA framework for quantum circuit synthesis. By analyzing how different mutations transform circuits, it identifies strategies that enhance efficiency and performance. Experiments utilized a fitness function emphasizing fidelity, while accounting for circuit depth and T-operations, to optimize circuits with four to six qubits. Our analysis revealed that, while the "swap, addition" strategy achieved the highest fidelity scores, it consistently increased circuit depth. In contrast, combining "swap, addition, delete" strategies offers a more balanced approach, delivering near-optimal results while also having the potential of reducing circuit depth.

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