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arXiv · 1504.07251

Universal recovery map for approximate Markov chains

David Sutter·Omar Fawzi·Renato Renner
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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 $ρ_{ABC}$ can be bounded from below by its distance to the closest recovered state $\mathcal{R}_{B \to BC}(ρ_{AB})$, where the $C$-part is reconstructed from the $B$-part only and the recovery map $\mathcal{R}_{B \to BC}$ merely depends on $ρ_{BC}$. One particular application of this result implies the equivalence between two different approaches to define topological order in quantum systems.

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David Sutter, Omar Fawzi, Renato Renner. 2015-09-23. Universal recovery map for approximate Markov chains. https://doi.org/10.1098/rspa.2015.0623

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