Beyond quantum Shannon decomposition: Circuit construction for n-qubit gates based on block-ZXZ decomposition

IF 3.8 2区 物理与天体物理 Q2 PHYSICS, APPLIED
Anna M. Krol, Zaid Al-Ars
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引用次数: 0

Abstract

This paper proposes an optimized quantum block-ZXZ decomposition method that results in more optimal quantum circuits than the quantum Shannon decomposition, which was presented in 2005 by M. Möttönen, and J. J. Vartiainen [in Trends in quantum computing research, edited by S. Shannon (Nova Science Publishers, 2006) Chap. 7, p. 149, arXiv:quant-ph/0504100]. The decomposition is applied recursively to generic quantum gates, and can take advantage of existing and future small-circuit optimizations. Because our method uses only single-qubit gates and uniformly controlled rotation-Z gates, it can easily be adapted to use other types of multi-qubit gates. With the proposed decomposition, a general three-qubit gate can be decomposed using 19 cnot gates (rather than 20). For general n-qubit gates, the proposed decomposition generates circuits that have 22484n322n+53 cnot gates, which is less than the best-known exact decomposition algorithm by (4n21)/3 cnot gates.

Abstract Image

超越量子香农分解:基于块-ZXZ分解的 n 量子位门电路构建
本文提出了一种优化的量子块-ZXZ分解方法,它比 M. Möttönen 和 J. J. Vartiainen 于 2005 年提出的量子香农分解方法[见 S. Shannon 编辑的《量子计算研究趋势》(新星科学出版社,2006 年)第 7 章第 149 页,arXiv:quant-ph/0504100]能产生更优化的量子电路。该分解方法可递归应用于通用量子门,并能利用现有和未来的小电路优化。由于我们的方法只使用单量子比特门和均匀控制的旋转-Z 门,因此很容易调整为使用其他类型的多量子比特门。使用我们提出的分解方法,一般的三量子位门可以用 19 个 cnot 门(而不是 20 个)来分解。对于一般的 n-qubit 门,所提出的分解方法生成的电路有 22484n-322n+53 个 cnot 门,比最著名的精确分解算法少 (4n-2-1)/3 个 cnot 门。
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来源期刊
Physical Review Applied
Physical Review Applied PHYSICS, APPLIED-
CiteScore
7.80
自引率
8.70%
发文量
760
审稿时长
2.5 months
期刊介绍: Physical Review Applied (PRApplied) publishes high-quality papers that bridge the gap between engineering and physics, and between current and future technologies. PRApplied welcomes papers from both the engineering and physics communities, in academia and industry. PRApplied focuses on topics including: Biophysics, bioelectronics, and biomedical engineering, Device physics, Electronics, Technology to harvest, store, and transmit energy, focusing on renewable energy technologies, Geophysics and space science, Industrial physics, Magnetism and spintronics, Metamaterials, Microfluidics, Nonlinear dynamics and pattern formation in natural or manufactured systems, Nanoscience and nanotechnology, Optics, optoelectronics, photonics, and photonic devices, Quantum information processing, both algorithms and hardware, Soft matter physics, including granular and complex fluids and active matter.
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