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A Hierarchy of Information Quantities for Finite Block Length Analysis of Quantum Tasks

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arxiv 1208.1478 v3 pith:VHQWBSHL submitted 2012-08-07 quant-ph

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keywords informationquantumtasksentropiesquantitiesblockcalculatefinite
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We consider two fundamental tasks in quantum information theory, data compression with quantum side information as well as randomness extraction against quantum side information. We characterize these tasks for general sources using so-called one-shot entropies. We show that these characterizations - in contrast to earlier results - enable us to derive tight second order asymptotics for these tasks in the i.i.d. limit. More generally, our derivation establishes a hierarchy of information quantities that can be used to investigate information theoretic tasks in the quantum domain: The one-shot entropies most accurately describe an operational quantity, yet they tend to be difficult to calculate for large systems. We show that they asymptotically agree up to logarithmic terms with entropies related to the quantum and classical information spectrum, which are easier to calculate in the i.i.d. limit. Our techniques also naturally yields bounds on operational quantities for finite block lengths.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Error Exponents for Quantum Packing Problems via An Operator Layer Cake Theorem

    quant-ph 2025-07 accept novelty 8.0 of 10

    The authors prove the Burnashev-Holevo conjecture by deriving a finite-blocklength random coding bound with a dimension-independent prefactor for classical-quantum channels, using a new operator layer cake theorem.

  2. Multiple Quantum Hypothesis Testing: One-Shot Pairwise Bounds and Sharp Asymptotics

    quant-ph 2026-06 unverdicted novelty 7.0 of 10

    Establishes dimension-free one-shot pairwise bounds for multiple quantum hypothesis testing, resolves Audenaert-Mosonyi conjecture, and proves achievability of multiple quantum Chernoff distance for arbitrary separabl...

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