One-Shot Distributed Source Simulation: As Quantum as it Can Get.

Ian George, Min-Hsiu Hsieh, Eric Chitambar
ISIT 2023, accepted on April 15, 2023.


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.