Convex-Split and Hypothesis Testing Approach to One-Shot Quantum Measurement Compression and Randomness Extraction

This paper concerns the problem of quantum measurement compression with side information in the one-shot setting with shared-randomness. In this problem, Alice shares a pure quantum state with Bob and the reference system. She performs a measurement on her registers and wishes to communicate the outcome to Bob using shared-randomness and classical communication. The outcome that Bob receives must be correctly correlated with the reference system and his own registers. Our goal is to concurrently minimize the classical communication and shared-randomness cost. The suggested protocol presented in this paper is based on convex-split and position based decoding. The communication is upper bounded in terms of smooth max and hypothesis testing relative entropies. A second protocol addresses the task of strong randomness extraction in the presence of quantum side information. The protocol provides an error guarantee in terms of relative entropy (as opposed to trace distance) and extracts close to the optimal number of uniform bits. As an application, we provide a new achievability result for the task of quantum measurement compression without feedback, in which Alice does not need to know the outcome of the measurement. The result achieves the optimal number of bits communicated and the required number of bits of shared-randomness, for the same task in the asymptotic and i.i.d. setting.