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A Hierarchy of Information Quantities for Finite Block Length Analysis of Quantum Tasks

机译:量子任务的有限块长分析的信息量层次结构

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摘要

We consider two fundamental tasks in quantum information theory, data compression with quantum side information, as well as randomness extraction against quantum side information. We characterize these tasks for general sources using so-called one-shot entropies. These characterizations—in contrast to earlier results—enable us to derive tight second-order asymptotics for these tasks in the i.i.d. limit. More generally, our derivation establishes a hierarchy of information quantities that can be used to investigate information theoretic tasks in the quantum domain: The one-shot entropies most accurately describe an operational quantity, yet they tend to be difficult to calculate for large systems. We show that they asymptotically agree (up to logarithmic terms) with entropies related to the quantum and classical information spectrum, which are easier to calculate in the i.i.d. limit. Our technique also naturally yields bounds on operational quantities for finite block lengths.
机译:我们考虑了量子信息理论中的两个基本任务,即利用量子辅助信息进行数据压缩以及针对量子辅助信息的随机性提取。我们使用所谓的单次熵来表征这些任务的一般来源。与先前的结果相反,这些特征使我们能够为i.i.d中的这些任务得出严格的二阶渐近性。限制。更一般而言,我们的推导建立了可用于研究量子域中信息理论任务的信息量层次结构:单次熵最准确地描述了操作量,但对于大型系统而言,它们往往难以计算。我们表明,它们与与量子和经典信息谱有关的熵渐近地一致(最多对数项),这在i.i.d中更容易计算。限制。我们的技术也自然会产生有限块长度的操作量边界。

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