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从雷尼熵功率到量子态的信息扫描

From Rényi Entropy Power to Information Scan of Quantum States.

作者信息

Jizba Petr, Dunningham Jacob, Prokš Martin

机构信息

FNSPE, Czech Technical University in Prague, Břehová 7, 115 19 Praha 1, Czech Republic.

Department of Physics and Astronomy, University of Sussex, Brighton BN1 9QH, UK.

出版信息

Entropy (Basel). 2021 Mar 12;23(3):334. doi: 10.3390/e23030334.

Abstract

In this paper, we generalize the notion of Shannon's entropy power to the Rényi-entropy setting. With this, we propose generalizations of the de Bruijn identity, isoperimetric inequality, or Stam inequality. This framework not only allows for finding new estimation inequalities, but it also provides a convenient technical framework for the derivation of a one-parameter family of Rényi-entropy-power-based quantum-mechanical uncertainty relations. To illustrate the usefulness of the Rényi entropy power obtained, we show how the information probability distribution associated with a quantum state can be reconstructed in a process that is akin to quantum-state tomography. We illustrate the inner workings of this with the so-called "cat states", which are of fundamental interest and practical use in schemes such as quantum metrology. Salient issues, including the extension of the notion of entropy power to Tsallis entropy and ensuing implications in estimation theory, are also briefly discussed.

摘要

在本文中,我们将香农熵功率的概念推广到雷尼熵的情形。据此,我们提出了德布鲁因恒等式、等周不等式或斯坦姆不等式的推广形式。该框架不仅有助于发现新的估计不等式,还为推导基于雷尼熵功率的单参数量子力学不确定性关系族提供了便利的技术框架。为了说明所得到的雷尼熵功率的有用性,我们展示了如何在类似于量子态层析成像的过程中重构与量子态相关的信息概率分布。我们用所谓的“猫态”来说明这一过程的内部机制,“猫态”在诸如量子计量学等方案中具有根本重要性和实际用途。我们还简要讨论了一些突出问题,包括熵功率概念向Tsallis熵的扩展以及在估计理论中的后续影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2db1/8001603/e53bffc6f848/entropy-23-00334-g001.jpg

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