论文标题
量子记忆辅助可观察的估计
Quantum memory assisted observable estimation
论文作者
论文摘要
估计多数可观察物是量子信息处理的重要任务。通常,通常适用的方法是将可观测值分解为多量值Pauli字符串的加权总和,即单价Pauli矩阵的张量产物,可以很容易地通过单量子旋转来测量。但是,在这种方法中,射击噪声的积累严重限制了有限数量测量的可实现差异。我们介绍了一种新颖的方法,称为连贯的Pauli求和(CPS),该方法通过利用对单量量子存储器的访问来规避这种限制,其中可以存储和积累测量信息。我们的算法可减少给定方差所需的测量数量,该测量值与分解可观察的Pauli字符串数量线性缩放。我们的工作表明,单个长期量子标程内存如何在基本任务中有助于噪音多数量子设备的操作。
The estimation of many-qubit observables is an essential task of quantum information processing. The generally applicable approach is to decompose the observables into weighted sums of multi-qubit Pauli strings, i.e., tensor products of single-qubit Pauli matrices, which can readily be measured with single qubit rotations. The accumulation of shot noise in this approach, however, severely limits the achievable variance for a finite number of measurements. We introduce a novel method, dubbed Coherent Pauli Summation (CPS) that circumvents this limitation by exploiting access to a single-qubit quantum memory in which measurement information can be stored and accumulated. Our algorithm offers a reduction in the required number of measurements for a given variance that scales linearly with the number of Pauli strings of the decomposed observable. Our work demonstrates how a single long-coherence qubit memory can assist the operation of noisy many-qubit quantum devices in a cardinal task.