The information-theoretic costs of simulating quantum measurements
Mark M. Wilde, Patrick Hayden, Francesco Buscemi, and Min-Hsiu Hsieh

TL;DR
This paper reviews Winter's measurement compression theorem, extends it to non-feedback scenarios, and introduces a new protocol involving quantum side information with applications in quantum information processing.
Contribution
It provides a comprehensive review of the measurement compression theorem, extends it to non-feedback cases, and introduces a new protocol with quantum side information and practical applications.
Findings
Extended the measurement compression theorem to non-feedback scenarios.
Proved a single-letter converse theorem demonstrating optimality.
Introduced a new protocol for measurement compression with quantum side information.
Abstract
Winter's measurement compression theorem stands as one of the most penetrating insights of quantum information theory (QIT). In addition to making an original and profound statement about measurement in quantum theory, it also underlies several other general protocols in QIT. In this paper, we provide a full review of Winter's measurement compression theorem, detailing the information processing task, giving examples for understanding it, reviewing Winter's achievability proof, and detailing a new approach to its single-letter converse theorem. We prove an extension of the theorem to the case in which the sender is not required to receive the outcomes of the simulated measurement. The total cost of common randomness and classical communication can be lower for such a "non-feedback" simulation, and we prove a single-letter converse theorem demonstrating optimality. We then review the…
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