161 research outputs found
Duality of privacy amplification against quantum adversaries and data compression with quantum side information
We show that the tasks of privacy amplification against quantum adversaries
and data compression with quantum side information are dual in the sense that
the ability to perform one implies the ability to perform the other. These are
two of the most important primitives in classical information theory, and are
shown to be connected by complementarity and the uncertainty principle in the
quantum setting. Applications include a new uncertainty principle formulated in
terms of smooth min- and max-entropies, as well as new conditions for
approximate quantum error correction.Comment: v2: Includes a derivation of an entropic uncertainty principle for
smooth min- and max-entropies. Discussion of the
Holevo-Schumacher-Westmoreland theorem remove
Convex-split and hypothesis testing approach to one-shot quantum measurement compression and randomness extraction
We consider the problem of quantum measurement compression with side
information in the one-shot setting with shared randomness. In this problem,
Alice shares a pure state with Reference and Bob and she performs a measurement
on her registers. She wishes to communicate the outcome of this measurement to
Bob using shared randomness and classical communication, in such a way that the
outcome that Bob receives is correctly correlated with Reference and Bob's own
registers. Our goal is to simultaneously minimize the classical communication
and randomness cost. We provide a protocol based on convex-split and position
based decoding with its communication upper bounded in terms of smooth max and
hypothesis testing relative entropies.
We also study the randomness cost of our protocol in both one-shot and
asymptotic and i.i.d. setting. By generalizing the convex-split technique to
incorporate pair-wise independent random variables, we show that our one shot
protocol requires small number of bits of shared randomness. This allows us to
construct a new protocol in the asymptotic and i.i.d. setting, which is optimal
in both the number of bits of communication and the number of bits of shared
randomness required.
We construct a new protocol for the task of strong randomness extraction in
the presence of quantum side information. Our protocol achieves error guarantee
in terms of relative entropy (as opposed to trace distance) and extracts close
to optimal number of uniform bits. As an application, we provide new
achievability result for the task of quantum measurement compression without
feedback, in which Alice does not need to know the outcome of the measurement.
This leads to the optimal number of bits communicated and number of bits of
shared randomness required, for this task in the asymptotic and i.i.d. setting.Comment: version 5: 29 pages, 1 figure. Added applications to randomness
extraction (against quantum side information) and measurement compression
without feedbac
Tight Finite-Key Analysis for Quantum Cryptography
Despite enormous progress both in theoretical and experimental quantum
cryptography, the security of most current implementations of quantum key
distribution is still not established rigorously. One of the main problems is
that the security of the final key is highly dependent on the number, M, of
signals exchanged between the legitimate parties. While, in any practical
implementation, M is limited by the available resources, existing security
proofs are often only valid asymptotically for unrealistically large values of
M. Here, we demonstrate that this gap between theory and practice can be
overcome using a recently developed proof technique based on the uncertainty
relation for smooth entropies. Specifically, we consider a family of
Bennett-Brassard 1984 quantum key distribution protocols and show that security
against general attacks can be guaranteed already for moderate values of M.Comment: 11 pages, 2 figure
The apex of the family tree of protocols: Optimal rates and resource inequalities
We establish bounds on the maximum entanglement gain and minimum quantum
communication cost of the Fully Quantum Slepian-Wolf protocol in the one-shot
regime, which is considered to be at the apex of the existing family tree in
Quantum Information Theory. These quantities, which are expressed in terms of
smooth min- and max-entropies, reduce to the known rates of quantum
communication cost and entanglement gain in the asymptotic i.i.d. scenario. We
also provide an explicit proof of the optimality of these asymptotic rates. We
introduce a resource inequality for the one-shot FQSW protocol, which in
conjunction with our results, yields achievable one-shot rates of its children
protocols. In particular, it yields bounds on the one-shot quantum capacity of
a noisy channel in terms of a single entropic quantity, unlike previously
bounds. We also obtain an explicit expression for the achievable rate for
one-shot state redistribution.Comment: 31 pages, 2 figures. Published versio
Identifying the Information Gain of a Quantum Measurement
We show that quantum-to-classical channels, i.e., quantum measurements, can
be asymptotically simulated by an amount of classical communication equal to
the quantum mutual information of the measurement, if sufficient shared
randomness is available. This result generalizes Winter's measurement
compression theorem for fixed independent and identically distributed inputs
[Winter, CMP 244 (157), 2004] to arbitrary inputs, and more importantly, it
identifies the quantum mutual information of a measurement as the information
gained by performing it, independent of the input state on which it is
performed. Our result is a generalization of the classical reverse Shannon
theorem to quantum-to-classical channels. In this sense, it can be seen as a
quantum reverse Shannon theorem for quantum-to-classical channels, but with the
entanglement assistance and quantum communication replaced by shared randomness
and classical communication, respectively. The proof is based on a novel
one-shot state merging protocol for "classically coherent states" as well as
the post-selection technique for quantum channels, and it uses techniques
developed for the quantum reverse Shannon theorem [Berta et al., CMP 306 (579),
2011].Comment: v2: new result about non-feedback measurement simulation, 45 pages, 4
figure
A Hierarchy of Information Quantities for Finite Block Length Analysis of Quantum Tasks
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.Comment: See also arXiv:1208.1400, which independently derives part of our
result: the second order asymptotics for binary hypothesis testin
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