Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-40084-1_19
Title: Achieving the limits of the noisy-storage model using entanglement sampling
Authors: Dupuis, F.
Fawzi, O.
Wehner, S. 
Issue Date: 2013
Citation: Dupuis, F.,Fawzi, O.,Wehner, S. (2013). Achieving the limits of the noisy-storage model using entanglement sampling. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8043 LNCS (PART 2) : 326-343. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-40084-1_19
Abstract: A natural measure for the amount of quantum information that a physical system E holds about another system A = A1,...,An is given by the min-entropy Hmin (A|E). Specifically, the min-entropy measures the amount of entanglement between E and A, and is the relevant measure when analyzing a wide variety of problems ranging from randomness extraction in quantum cryptography, decoupling used in channel coding, to physical processes such as thermalization or the thermodynamic work cost (or gain) of erasing a quantum system. As such, it is a central question to determine the behaviour of the min-entropy after some process M is applied to the system A. Here we introduce a new generic tool relating the resulting min-entropy to the original one, and apply it to several settings of interest, including sampling of subsystems and measuring in a randomly chosen basis. The results on random measurements yield new high-order entropic uncertainty relations with which we prove the optimality of cryptographic schemes in the bounded quantum storage model. This is an abridged version of the paper; the full version containing all proofs and further applications can be found in [13]. © 2013 International Association for Cryptologic Research.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/77997
ISBN: 9783642400834
ISSN: 03029743
DOI: 10.1007/978-3-642-40084-1_19
Appears in Collections:Staff Publications

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