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Quantum Physics

arXiv:2504.02632 (quant-ph)
[Submitted on 3 Apr 2025 (v1) , last revised 25 Apr 2025 (this version, v2)]

Title: A Scalable Synthesis Algorithm for Reversible Functions

Title: 可逆函数的可扩展合成算法

Authors:Moein Sarvaghad-Moghaddam, Morteza Saheb Zamani, Mehdi Sedighi
Abstract: Reversible computation is an emerging technology that has gained significant attention due to its critical role in quantum circuit synthesis and low-power design. This paper introduces a transformation-based method for exact synthesis of reversible circuits. The proposed approach utilizes a novel adaptation of the Quine-McCluskey algorithm to eliminate input-output discrepancies in the truth table, transforming the permutation matrix into an identity matrix. Furthermore, a novel search space reduction technique is presented which, combined with the primary method, enables the synthesis algorithm to handle high-input reversible functions. This approach combines the influence of multiple control qubits on a target qubit, evaluating their collective impact. This aggregation can decrease the control qubit count within quantum gates. Consequently, it proves beneficial for applications like surface code error correction architectures as well as current Noisy Intermediate-Scale Quantum (NISQ) hardwares. Experimental results demonstrate significant improvements over the state-of-the-art exact synthesis methods, achieving up to 99% improvements in terms of the number of levels of T-gates.
Abstract: 可逆计算是一种新兴技术,由于其在量子电路综合和低功耗设计中的关键作用而引起了广泛关注。 本文介绍了一种基于变换的可逆电路精确综合方法。 所提出的方法利用了Quine-McCluskey算法的一种新颖适应形式,以消除真值表中的输入-输出差异,将置换矩阵转换为单位矩阵。 此外,还提出了一种新颖的搜索空间缩减技术,该技术与主要方法结合使用时,可以使综合算法处理高输入的可逆函数。 此方法结合了多个控制量子比特对目标量子比特的影响,评估它们的集体影响。 这种聚合可以减少量子门内的控制量子比特数量。 因此,这对表面码纠错架构以及当前的噪声中等规模量子(NISQ)硬件有益。 实验结果显示,与最先进的精确综合方法相比有显著改进,在T门级数方面最多提高了99%。
Subjects: Quantum Physics (quant-ph) ; Emerging Technologies (cs.ET); Performance (cs.PF)
Cite as: arXiv:2504.02632 [quant-ph]
  (or arXiv:2504.02632v2 [quant-ph] for this version)
  https://doi.org/10.48550/arXiv.2504.02632
arXiv-issued DOI via DataCite

Submission history

From: Moein Sarvaghad-Moghaddam [view email]
[v1] Thu, 3 Apr 2025 14:29:33 UTC (1,147 KB)
[v2] Fri, 25 Apr 2025 14:53:16 UTC (1,337 KB)
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