Distributed source simulation is the task where two (or more) parties share some correlated randomness and use local operations and no communication to convert this into some target correlation. Wyner's seminal result showed that asymptotically the rate of uniform shared randomness needed for this task is given by a mutual information induced measure, now referred to as Wyner's common information. This asymptotic result was extended by Hayashi in the quantum setting to separable states, the largest class of states for which this task can be performed. In this work we characterize this task in the one-shot setting using the smooth entropy framework. We do this by introducing one-shot operational quantities and correlation measures that characterize them. We establish asymptotic equipartition properties for our correlation measures thereby recovering, and in fact strengthening, the aforementioned asymptotic results. In doing so, we consider technical points in one-shot network information theory and generalize the support lemma to the classical-quantum setting. We also introduce entanglement versions of the distributed source simulation task and determine bounds in this setting via quantum embezzling.
翻译:分布源模拟是两个( 或更多) 双方共享某种相关随机性并使用本地操作且没有通信将它转换成某些目标关联的任务。 Wyner 的开创性结果表明, 任务所需的统一共享随机性率通过相互信息诱导的措施( 现称Wyner的共同信息 ) 来进行。 由林林在量子设置中将无症状结果推广到可分离状态, 即执行此任务的最大类国家 。 在这项工作中, 我们使用光滑的 entropy 框架在一拍 设置中描述这一任务。 我们这样做的方法是引入一发操作量和相应措施, 从而恢复并实际上加强上述的对应措施。 在这样做时, 我们考虑一发网络信息理论中的技术点, 并将支持元素一般化到古典- Quantum 设置中。 我们还引入了分布源模拟任务的连接版本, 并通过量子组合决定此设置的界限 。