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密度矩阵的平方根统计及其应用

Square Root Statistics of Density Matrices and Their Applications.

作者信息

Ye Lyuzhou, Huang Youyi, Osborn James C, Wei Lu

机构信息

Department of Computer Science, Texas Tech University, Lubbock, TX 79409, USA.

Computational Science Division, Argonne National Laboratory, Argonne, IL 60439, USA.

出版信息

Entropy (Basel). 2024 Jan 12;26(1):0. doi: 10.3390/e26010068.

Abstract

To estimate the degree of quantum entanglement of random pure states, it is crucial to understand the statistical behavior of entanglement indicators such as the von Neumann entropy, quantum purity, and entanglement capacity. These entanglement metrics are functions of the spectrum of density matrices, and their statistical behavior over different generic state ensembles have been intensively studied in the literature. As an alternative metric, in this work, we study the sum of the square root spectrum of density matrices, which is relevant to negativity and fidelity in quantum information processing. In particular, we derive the finite-size mean and variance formulas of the sum of the square root spectrum over the Bures-Hall ensemble, extending known results obtained recently over the Hilbert-Schmidt ensemble.

摘要

为了估计随机纯态的量子纠缠程度,理解诸如冯·诺依曼熵、量子纯度和纠缠容量等纠缠指标的统计行为至关重要。这些纠缠度量是密度矩阵谱的函数,并且它们在不同的一般态系综上的统计行为在文献中已得到深入研究。作为一种替代度量,在本工作中,我们研究密度矩阵平方根谱的总和,它与量子信息处理中的负性和保真度相关。特别地,我们推导了在布雷斯 - 霍尔系综上平方根谱总和的有限尺寸均值和方差公式,扩展了最近在希尔伯特 - 施密特系综上得到的已知结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/82b9/11154417/df9d97e647f9/entropy-26-00068-g001.jpg

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