量子傅里叶变换具有小纠缠

IF 9.3 Q1 PHYSICS, APPLIED
Jielun Chen, E.M. Stoudenmire, Steven R. White
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引用次数: 11

摘要

量子傅里叶变换(QFT)是许多重要量子算法的关键组成部分,其中最著名的是用于质数乘积分解的Shor算法的基本组成部分。鉴于其卓越的能力,人们会认为它可以为量子比特系统引入大纠缠,并且很难进行经典模拟。虽然早期的结果表明QFT确实具有最大的算子纠缠,但我们表明这完全是由于QFT中的位反转。QFT的核心部分施密特系数呈指数级快速衰减,因此无论量子比特的数量如何,它都只能产生恒定数量的纠缠。此外,我们还证明了QFT的纠缠功率与具有指数衰减相互作用的哈密顿量的时间演化相同,因此可以使用动力学面积定律的一个变体来直观地理解低纠缠。利用量子傅立叶变换的低纠缠特性,我们证明了量子傅立叶变换在低键维矩阵积态上的经典模拟在量子比特的数量上是线性的,这比经典的快速傅立叶变换在许多类函数上提供了潜在的加速。我们在一些简单函数的测试计算中演示了这种加速。对于长度为106-108的数据向量,加速可以达到几个数量级根据知识共享署名4.0国际许可协议,美国物理学会doi:https://doi.org/10.1103/PRXQuantum.4.040318Published。这项工作的进一步分发必须保持作者的归属和已发表文章的标题,期刊引用和DOI。发表于美国物理学会物理学科标题(PhySH)研究领域纠缠熵纠缠测量纠缠产生量子算法与计算量子电路量子计算量子信息中的量子关联量子关联基础与形式化量子纠缠量子信息理论技术矩阵积态传感器网络方法量子信息科学技术能源科学技术
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Quantum Fourier Transform Has Small Entanglement

Quantum Fourier Transform Has Small Entanglement
The quantum Fourier transform (QFT) is a key component of many important quantum algorithms, most famously being the essential ingredient in Shor’s algorithm for factoring products of primes. Given its remarkable capability, one would think it can introduce large entanglement to qubit systems and would be difficult to simulate classically. While early results showed the QFT indeed has maximal operator entanglement, we show that this is entirely due to the bit reversal in the QFT. The core part of the QFT has Schmidt coefficients decaying exponentially quickly, and thus it can generate only a constant amount of entanglement regardless of the number of qubits. In addition, we show the entangling power of the QFT is the same as the time evolution of a Hamiltonian with exponentially decaying interactions, and thus a variant of the area law for dynamics can be used to understand the low entanglement intuitively. Using the low entanglement property of the QFT, we show that classical simulations of the QFT on a matrix product state with low bond dimension take time linear in the number of qubits, providing a potential speedup over the classical fast Fourier transform on many classes of functions. We demonstrate this speedup in test calculations on some simple functions. For data vectors of length 106–108, the speedup can be a few orders of magnitude.2 MoreReceived 2 January 2023Accepted 25 September 2023DOI:https://doi.org/10.1103/PRXQuantum.4.040318Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Published by the American Physical SocietyPhysics Subject Headings (PhySH)Research AreasEntanglement entropyEntanglement measuresEntanglement productionQuantum algorithms & computationQuantum circuitsQuantum computationQuantum correlations in quantum informationQuantum correlations, foundations & formalismQuantum entanglementQuantum information theoryTechniquesMatrix product statesTensor network methodsQuantum Information, Science & TechnologyEnergy Science & Technology
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CiteScore
14.60
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