简化的量子近似计数

S. Aaronson, Patrick Rall
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引用次数: 101

摘要

1998年,Brassard, Hoyer, Mosca和Tapp (BHMT)给出了一个近似计数的量子算法。给定一个包含$N$项的列表,其中有$K$项被标记,它们的算法通过只进行$O\left( \frac{1}{\varepsilon}\sqrt{\frac{N}{K}}\right) $查询来估计$K$在相对误差$\varepsilon$之内。虽然这种加速是“Grover”类型的,但BHMT算法有一个奇怪的特点,即依赖于量子傅里叶变换(QFT),而量子傅里叶变换通常与肖尔算法联系在一起。这有必要吗?本文提出了一种简化算法,并证明了该算法仅使用Grover迭代即可实现相同的查询复杂度。我们还将其推广到无qft的幅度估计算法。之前,Grover、Abrams和Williams、Suzuki等人以及Wie(我们撰写本文时是后两位)概述了近似计数的相关方法,但在所有情况下都没有进行严格的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum Approximate Counting, Simplified
In 1998, Brassard, Hoyer, Mosca, and Tapp (BHMT) gave a quantum algorithm for approximate counting. Given a list of $N$ items, $K$ of them marked, their algorithm estimates $K$ to within relative error $\varepsilon$ by making only $O\left( \frac{1}{\varepsilon}\sqrt{\frac{N}{K}}\right) $ queries. Although this speedup is of "Grover" type, the BHMT algorithm has the curious feature of relying on the Quantum Fourier Transform (QFT), more commonly associated with Shor's algorithm. Is this necessary? This paper presents a simplified algorithm, which we prove achieves the same query complexity using Grover iterations only. We also generalize this to a QFT-free algorithm for amplitude estimation. Related approaches to approximate counting were sketched previously by Grover, Abrams and Williams, Suzuki et al., and Wie (the latter two as we were writing this paper), but in all cases without rigorous analysis.
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