474 research outputs found
Properties of Noncommutative Renyi and Augustin Information
The scaled R\'enyi information plays a significant role in evaluating the
performance of information processing tasks by virtue of its connection to the
error exponent analysis. In quantum information theory, there are three
generalizations of the classical R\'enyi divergence---the Petz's, sandwiched,
and log-Euclidean versions, that possess meaningful operational interpretation.
However, these scaled noncommutative R\'enyi informations are much less
explored compared with their classical counterpart, and lacking crucial
properties hinders applications of these quantities to refined performance
analysis. The goal of this paper is thus to analyze fundamental properties of
scaled R\'enyi information from a noncommutative measure-theoretic perspective.
Firstly, we prove the uniform equicontinuity for all three quantum versions of
R\'enyi information, hence it yields the joint continuity of these quantities
in the orders and priors. Secondly, we establish the concavity in the region of
for both Petz's and the sandwiched versions. This completes the
open questions raised by Holevo
[\href{https://ieeexplore.ieee.org/document/868501/}{\textit{IEEE
Trans.~Inf.~Theory}, \textbf{46}(6):2256--2261, 2000}], Mosonyi and Ogawa
[\href{https://doi.org/10.1007/s00220-017-2928-4/}{\textit{Commun.~Math.~Phys},
\textbf{355}(1):373--426, 2017}]. For the applications, we show that the strong
converse exponent in classical-quantum channel coding satisfies a minimax
identity. The established concavity is further employed to prove an entropic
duality between classical data compression with quantum side information and
classical-quantum channel coding, and a Fenchel duality in joint source-channel
coding with quantum side information in the forthcoming papers
A Generalized Typicality for Abstract Alphabets
A new notion of typicality for arbitrary probability measures on standard
Borel spaces is proposed, which encompasses the classical notions of weak and
strong typicality as special cases. Useful lemmas about strong typical sets,
including conditional typicality lemma, joint typicality lemma, and packing and
covering lemmas, which are fundamental tools for deriving many inner bounds of
various multi-terminal coding problems, are obtained in terms of the proposed
notion. This enables us to directly generalize lots of results on finite
alphabet problems to general problems involving abstract alphabets, without any
complicated additional arguments. For instance, quantization procedure is no
longer necessary to achieve such generalizations. Another fundamental lemma,
Markov lemma, is also obtained but its scope of application is quite limited
compared to others. Yet, an alternative theory of typical sets for Gaussian
measures, free from this limitation, is also developed. Some remarks on a
possibility to generalize the proposed notion for sources with memory are also
given.Comment: 44 pages; submitted to IEEE Transactions on Information Theor
Joint source-channel coding with feedback
This paper quantifies the fundamental limits of variable-length transmission
of a general (possibly analog) source over a memoryless channel with noiseless
feedback, under a distortion constraint. We consider excess distortion, average
distortion and guaranteed distortion (-semifaithful codes). In contrast to
the asymptotic fundamental limit, a general conclusion is that allowing
variable-length codes and feedback leads to a sizable improvement in the
fundamental delay-distortion tradeoff. In addition, we investigate the minimum
energy required to reproduce source samples with a given fidelity after
transmission over a memoryless Gaussian channel, and we show that the required
minimum energy is reduced with feedback and an average (rather than maximal)
power constraint.Comment: To appear in IEEE Transactions on Information Theor
One-shot lossy quantum data compression
We provide a framework for one-shot quantum rate distortion coding, in which
the goal is to determine the minimum number of qubits required to compress
quantum information as a function of the probability that the distortion
incurred upon decompression exceeds some specified level. We obtain a one-shot
characterization of the minimum qubit compression size for an
entanglement-assisted quantum rate-distortion code in terms of the smooth
max-information, a quantity previously employed in the one-shot quantum reverse
Shannon theorem. Next, we show how this characterization converges to the known
expression for the entanglement-assisted quantum rate distortion function for
asymptotically many copies of a memoryless quantum information source. Finally,
we give a tight, finite blocklength characterization for the
entanglement-assisted minimum qubit compression size of a memoryless isotropic
qubit source subject to an average symbol-wise distortion constraint.Comment: 36 page
Randomized Quantization and Source Coding with Constrained Output Distribution
This paper studies fixed-rate randomized vector quantization under the
constraint that the quantizer's output has a given fixed probability
distribution. A general representation of randomized quantizers that includes
the common models in the literature is introduced via appropriate mixtures of
joint probability measures on the product of the source and reproduction
alphabets. Using this representation and results from optimal transport theory,
the existence of an optimal (minimum distortion) randomized quantizer having a
given output distribution is shown under various conditions. For sources with
densities and the mean square distortion measure, it is shown that this optimum
can be attained by randomizing quantizers having convex codecells. For
stationary and memoryless source and output distributions a rate-distortion
theorem is proved, providing a single-letter expression for the optimum
distortion in the limit of large block-lengths.Comment: To appear in the IEEE Transactions on Information Theor
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