Characterizing Entanglement Dimensionality from Randomized Measurements

IF 9.3 Q1 PHYSICS, APPLIED
Shuheng Liu, Qiongyi He, M. Huber, O. Gühne, G. Vitagliano
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引用次数: 5

Abstract

We consider the problem of detecting the dimensionality of entanglement with the use of correlations between measurements in randomized directions. First, exploiting the recently derived covariance matrix criterion for the entanglement dimensionality [S. Liu et al., arXiv:2208.04909], we derive an inequality that resembles well-known entanglement criteria, but contains different bounds for the different dimensionalities of entanglement. This criterion is invariant under local changes of $su(d)$ bases and can be used to find regions in the space of moments of randomized correlations, generalizing the results of [S. Imai et al., Phys. Rev. Lett. 126, 150501 (2021)] to the case of entanglement-dimensionality detection. In particular, we find analytical boundary curves for the different entanglement dimensionalities in the space of second- and fourth-order moments of randomized correlations for all dimensions $d_a = d_b = d$ of a bipartite system. We then show how our method works in practice, also considering a finite statistical sample of correlations, and we also show that it can detect more states than other entanglement-dimensionality criteria available in the literature, thus providing a method that is both very powerful and potentially simpler in practical scenarios. We conclude by discussing the partly open problem of the implementation of our method in the multipartite scenario.
从随机测量中表征纠缠维数
我们考虑使用随机方向上测量之间的相关性来检测纠缠的维度的问题。首先,利用最近导出的纠缠维度的协方差矩阵准则[S.Liu等人,arXiv:2208.04909],我们导出了一个不等式,该不等式类似于众所周知的纠缠准则,但包含不同纠缠维度的不同边界。该标准在$su(d)$base的局部变化下是不变的,并且可以用于在随机相关的矩空间中寻找区域,将[S.Imai等人,Phys.Rev.Lett.126150501(2021)]的结果推广到纠缠维度检测的情况。特别地,我们在二分系统的所有维数$d_a=d_b=d$的随机关联的二阶和四阶矩空间中找到了不同纠缠维数的解析边界曲线。然后,我们展示了我们的方法在实践中是如何工作的,同时考虑了有限的相关性统计样本,我们还展示了它可以检测到比文献中可用的其他纠缠维度标准更多的状态,从而提供了一种在实际场景中非常强大且可能更简单的方法。最后,我们讨论了在多方场景中实现我们的方法的部分开放问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
14.60
自引率
0.00%
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