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Universal recovery map for approximate Markov chains.

ABSTRACT: A central question in quantum information theory is to determine how well lost information can be reconstructed. Crucially, the corresponding recovery operation should perform well without knowing the information to be reconstructed. In this work, we show that the quantum conditional mutual information measures the performance of such recovery operations. More precisely, we prove that the conditional mutual information I(A:C|B) of a tripartite quantum state ?_ABC can be bounded from below by its distance to the closest recovered state [Formula: see text], where the C-part is reconstructed from the B-part only and the recovery map [Formula: see text] merely depends on ?_BC . One particular application of this result implies the equivalence between two different approaches to define topological order in quantum systems.

SUBMITTER: Sutter D

PROVIDER: S-EPMC4841654 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Universal recovery map for approximate Markov chains.

Sutter David D Fawzi Omar O Renner Renato R

Proceedings. Mathematical, physical, and engineering sciences 20160201 2186

A central question in quantum information theory is to determine how well lost information can be reconstructed. Crucially, the corresponding recovery operation should perform well without knowing the information to be reconstructed. In this work, we show that the quantum conditional mutual information measures the performance of such recovery operations. More precisely, we prove that the conditional mutual information I(A:C|B) of a tripartite quantum state ...[more]

PMID: 27118889

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Dataset Information

Universal recovery map for approximate Markov chains.

Publications

Universal recovery map for approximate Markov chains.

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