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关于量子比特系统多参数估计问题的量子性

On the Quantumness of Multiparameter Estimation Problems for Qubit Systems.

作者信息

Razavian Sholeh, Paris Matteo G A, Genoni Marco G

机构信息

Faculty of Physics, Azarbaijan Shahid Madani University, Tabriz 5375171379, Iran.

Quantum Technology Lab, Dipartimento di Fisica "Aldo Pontremoli", Università degli Studi di Milano, I-20133 Milano, Italy.

出版信息

Entropy (Basel). 2020 Oct 23;22(11):1197. doi: 10.3390/e22111197.

Abstract

The estimation of more than one parameter in quantum mechanics is a fundamental problem with relevant practical applications. In fact, the ultimate limits in the achievable estimation precision are ultimately linked with the non-commutativity of different observables, a peculiar property of quantum mechanics. We here consider several estimation problems for qubit systems and evaluate the corresponding R, a measure that has been recently introduced in order to quantify how incompatible the parameters to be estimated are. In particular, R is an upper bound for the renormalized difference between the (asymptotically achievable) Holevo bound and the SLD Cramér-Rao bound (i.e., the matrix generalization of the single-parameter quantum Cramér-Rao bound). For all the estimation problems considered, we evaluate the quantumness R and, in order to better understand its usefulness in characterizing a multiparameter quantum statistical model, we compare it with the renormalized difference between the Holevo and the SLD-bound. Our results give evidence that R is a useful quantity to characterize multiparameter estimation problems, as for several quantum statistical model, it is equal to the difference between the bounds and, in general, their behavior qualitatively coincide. On the other hand, we also find evidence that, for certain quantum statistical models, the bound is not in tight, and thus R may overestimate the degree of quantum incompatibility between parameters.

摘要

在量子力学中估计多个参数是一个具有相关实际应用的基本问题。事实上,可实现估计精度的最终极限最终与不同可观测量的非对易性相关联,这是量子力学的一个独特性质。我们在此考虑量子比特系统的几个估计问题,并评估相应的R,R是最近引入的一种度量,用于量化待估计参数的不相容程度。特别地,R是(渐近可达到的)霍列沃界与对称对数导数(SLD)克拉美罗界(即单参数量子克拉美罗界的矩阵推广)之间的重整化差异的上界。对于所考虑的所有估计问题,我们评估量子性R,并且为了更好地理解其在表征多参数量子统计模型中的有用性,我们将其与霍列沃界和SLD界之间的重整化差异进行比较。我们的结果表明,对于几个量子统计模型,R是表征多参数估计问题的一个有用量,因为它等于界之间的差异,并且一般来说,它们的行为在定性上是一致的。另一方面,我们也发现,对于某些量子统计模型,该界并不紧密,因此R可能高估了参数之间的量子不相容程度。

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