arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2103.02404quant-phcs.ITmath-phmath.ITmath.MP

量子网络辨识

Quantum Network Discrimination

Christoph Hirche

AI总结:

该研究聚焦量子网络辨识这一量子信息论新方向,以量子超信道为基础模型,分析多副本下的策略类别,给出非对称辨识的渐近速率界,还拓展至对称辨识、强逆指数等场景并给出应用。

摘要:

对象辨识,尤其是量子态辨识,是(量子)信息论中最基础的任务之一。近年来,将该框架拓展至点到点量子信道的研究已取得显著进展。然而,随着技术进步,该领域的研究重心正转向更复杂的结构:量子网络。与信道不同,量子网络设有中间接入点,信息可在这些节点被接收、处理并重新注入网络。本工作研究量子网络辨识及其基本限制。尤其当可多次使用网络时,可用策略的集合会变得愈发复杂。能体现该问题结构的最简单量子网络是量子超信道(quantum superchannel)。我们讨论了考虑n份超信道副本时的可用策略类别,并给出了非对称辨识场景下渐近可达速率的基本界。此外,我们还探讨了可达性、对称网络辨识、强逆指数、向任意量子网络的推广,最后介绍了在主动版量子照明(quantum illumination)问题中的一项应用。

英文摘要:

Discrimination between objects, in particular quantum states, is one of the most fundamental tasks in (quantum) information theory. Recent years have seen significant progress towards extending the framework to point-to-point quantum channels. However, with technological progress the focus of the field is shifting to more complex structures: Quantum networks. In contrast to channels, networks allow for intermediate access points where information can be received, processed and reintroduced into the network. In this work we study the discrimination of quantum networks and its fundamental limitations. In particular when multiple uses of the network are at hand, the rooster of available strategies becomes increasingly complex. The simplest quantum network that capturers the structure of the problem is given by a quantum superchannel. We discuss the available classes of strategies when considering $n$ copies of a superchannel and give fundamental bounds on the asymptotically achievable rates in an asymmetric discrimination setting. Furthermore, we discuss achievability, symmetric network discrimination, the strong converse exponent, generalization to arbitrary quantum networks and finally an application to an active version of the quantum illumination problem.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑