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Partially Smoothed Information Measures

Anurag Anshu, Mario Berta, Rahul Jain, Marco Tomamichel

2020IEEE Transactions on Information Theory22 citationsDOIOpen Access PDF

Abstract

Smooth entropies are a tool for quantifying resource trade-offs in (quantum) information theory and cryptography. In typical bi- and multi-partite problems, however, some of the sub-systems are often left unchanged and this is not reflected by the standard smoothing of information measures over a ball of close states. We propose to smooth instead only over a ball of close states which also have some of the reduced states on the relevant sub-systems fixed. This partial smoothing of information measures naturally allows to give more refined characterizations of various information-theoretic problems in the one-shot setting. In particular, we immediately get asymptotic second-order characterizations for tasks such as privacy amplification against classical side information or classical state splitting. For quantum problems like state merging the general resource trade-off is tightly characterized by partially smoothed information measures as well.

Topics & Concepts

SmoothingInformation theoryComputer scienceMathematicsBall (mathematics)State (computer science)Entropy (arrow of time)AlgorithmTheoretical computer scienceStatistical physicsApplied mathematicsQuantumQuantum informationCoherent informationMeasure (data warehouse)General theoryQuantum stateInformation resourceMathematical optimizationComplete informationQuantum entanglementState informationQuantum Information and CryptographyQuantum Mechanics and ApplicationsQuantum Computing Algorithms and Architecture
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