一项反驳QSVT的案例研究：通过信号处理技术改进的量子相位估计评估
A case study against QSVT: assessment of quantum phase estimation improved by signal processing techniques
AI总结：
本研究系统对比了最大化量子相位估计成功概率的QSVT与窗函数方法，发现后者以约1/4查询成本实现3-5个数量级的成功概率提升，指出QPE无法从QSVT整合中获益，Kaiser窗函数是当前高成功率QPE的最实用选择。
摘要：
近年来，学界提出了将量子相位估计（QPE）作为无测量子例程连贯使用的量子算法。为有效实现这一点，该例程必须能以接近1的成功概率区分本征态。本文首次系统比较了两种最大化该成功概率的方法：一种使用量子奇异值变换（QSVT），另一种利用窗函数——此前窗函数被作为相位值分布的先验进行研究。我们发现，量子奇异值变换的表现远逊于窗函数方法，后者能将成功概率提升3至5个数量级，而查询成本约为前者的1/4。我们的电路仿真结果表明，QPE并非一个能从QSVT整合中获益的领域，且我们证明，使用Kaiser窗函数是目前实现高成功概率QPE的最实用选择。
英文摘要：
In recent years, quantum algorithms have been proposed which use quantum phase estimation (QPE) coherently as a subroutine without measurement. In order to do this effectively, the routine must be able to distinguish eigenstates with success probability close to unity. In this paper, we provide the first systematic comparison between two approaches towards maximizing this success probability, one using the quantum singular value transform and the other leveraging window functions, which have been previously studied as priors of the phase value distribution. We find that the quantum singular value transform is significantly outclassed by the window function approach, with the latter able to achieve between 3 and 5 orders of magnitude improvement in the success probability with approximately 1/4 the query cost. Our circuit simulation results indicate that QPE is not a domain which benefits from the integration of QSVT and we show that the use of the Kaiser window function is currently the most practical choice for realizing QPE with high success probability.
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