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Information-disturbance trade-off in generalized entanglement swapping

2020/10/31 by Pratapaditya Bej, Arkaprabha Ghosal, Debarshi Das +2 · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #Bell's theorem #Combinatorics #Conditional mutual information #Diagonal #Geometry #Mathematical analysis #Mathematics #Mutual information #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum entanglement #Quantum mechanics #Separable space #Statistics #quant-ph

paper · pdf · doi:10.1103/physreva.102.052416

published as Phys. Rev. A 102, 052416 (2020) · 7 pages, 2 figures;v2: typos corrected, minor edits, published version

openalex publication_date 2020/11/19 · arxiv created 2020/11/20 · arxiv updated 2020/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

We study information-disturbance trade-off in generalized entanglement swapping protocols wherein starting from Bell pairs (1,2) and (3,4), one performs an arbitrary joint measurement on (2,3), so that (1,4) now becomes correlated. We obtain trade-off inequalities between information gain in correlations of (1,4) and residual information in correlations of (1,2) and (3,4), respectively, and we argue that information contained in correlations (information) is conserved if each inequality is an equality. We show that information is conserved for a maximally entangled measurement but is not conserved for any other complete orthogonal measurement and Bell measurement mixed with white noise. However, rather surprisingly, we find that information is conserved for rank-2 Bell diagonal measurements, although such measurements do not conserve entanglement. We also show that a separable measurement on (2,3) can conserve information, even if, as in our example, the post-measurement states of all three pairs (1,2), (3,4), and (1,4) become separable. This implies that correlations from an entangled pair can be transferred to separable pairs in nontrivial ways so that no information is lost in the process.

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