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October 20, 20250 citationsOpen Access

SSR: A Swapping-Sweeping-and-Rewriting Optimizer for Quantum Circuit Transformation

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YHYunqi HuangXZXiaohao ZhouFMFanwu Meng

Key Points

  • The optimizer significantly reduces the depth of quantum circuit transformation circuits, enhancing performance.
  • Results show a maximum depth reduction of 26.68% and an average reduction of 12.18% across benchmark circuits.
  • The approach utilizes a genetic algorithm to rearrange quantum circuits and optimize gate usage effectively.
  • These advancements highlight the potential for improved success rates in quantum computations with optimized circuits.

Abstract

Quantum circuit transformation (QCT), necessary for adapting any quantum circuit to the qubit connectivity constraints of the NISQ device, often introduces numerous additional SWAP gates into the original circuit, increasing the circuit depth and thus reducing the success rate of computation. To minimize the depth of QCT circuits, we propose a Swapping-Sweeping-and-Rewriting optimizer. This optimizer rearranges the circuit based on generalized gate commutation rules via a genetic algorithm, extracts subcircuits consisting of CNOT gates using a circuit sweeping technique, and rewrites each subcircuit with a functionally equivalent and depth-optimal circuit generated by an SAT solver. The devised optimizer effectively captures the intrinsic patterns of the QCT circuits, and the experimental results demonstrate that our algorithm can significantly reduce the depth of QCT circuits, 26.68\% at most and 12.18\% on average, across all benchmark circuits.

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Cite This Study

Huang et al. (2025) studied this question.

synapsesocial.com/papers/68f5fcce8d54a28a75cf1c5ahttps://doi.org/10.48550/arxiv.2503.03227
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