4.6 Article

Theory of channel simulation and bounds for private communication

期刊

QUANTUM SCIENCE AND TECHNOLOGY
卷 3, 期 3, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.1088/2058-9565/aac394

关键词

quantum channels; entanglement; quantum cryptography; Gaussian channels; quantum teleportation; quantum capacities

资金

  1. Innovation Fund Denmark (Qubiz project)
  2. European Union (MSCA-IF, EC grant) [745727]
  3. EPSRC [EP/K034480/1]
  4. EPSRC via the 'UK Quantum Communications Hub' [EP/M013472/1]
  5. EPSRC [EP/M013472/1] Funding Source: UKRI
  6. Marie Curie Actions (MSCA) [745727] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

We review recent results on the simulation of quantum channels, the reduction of adaptive protocols (teleportation stretching), and the derivation of converse bounds for quantum and private communication, as established in PLOB (Pirandola et al 2017 Nat. Commun. 8 15043). We start. by introducing a general weak converse bound for private communication based on the relative entropy of entanglement. We discuss how combining this bound with channel simulation and teleportation stretching, PLOB established the two-way quantum and private capacities of several fundamental channels, including the bosonic lossy channel. We then provide a rigorous proof of the strong converse property of these bounds by adopting a correct use of the Braunstein-Kimble teleportation protocol for the simulation of bosonic Gaussian channels. This analysis provides a full justification of claims presented in the follow-up paper WTB(Wilde et al 2017 IEEE Trans. Inf. Theory 63 1792-817) whose upper bounds for Gaussian channels would be otherwise infinitely large. Besides clarifying contributions in the area of channel simulation and protocol reduction, we also present some generalizations of the tools to other entanglement measures and novel results on the maximum excess noise which is tolerable in quantum key distribution.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据