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This article investigates sharp comparison of moments for various classes of random variables appearing in a geometric context. In the first part of our work we find the optimal constants in the Khintchine inequality for random vectors…

Functional Analysis · Mathematics 2018-10-11 Alexandros Eskenazis , Piotr Nayar , Tomasz Tkocz

We provide lower and upper bounds on the information transmission capacity of one single use of a classical-quantum channel. The lower bound is expressed in terms of the Hoeffding capacity, that we define similarly to the Holevo capacity,…

Quantum Physics · Physics 2009-07-24 Milan Mosonyi , Nilanjana Datta

The purpose of this work is to extend the result of previous papers quant-ph/9611023, quant-ph/9703013 to quantum channels with additive constraints onto the input signal, by showing that the capacity of such channel is equal to the…

Quantum Physics · Physics 2007-05-23 A. S. Holevo

This paper shows new general nonasymptotic achievability and converse bounds and performs their dispersion analysis for the lossy compression problem in which the compressor observes the source through a noisy channel. While this problem is…

Information Theory · Computer Science 2016-09-19 Victoria Kostina , Sergio Verdú

This paper first focuses on deriving an alternative approach for proving an extremal entropy inequality (EEI), originally presented in [11]. The proposed approach does not rely on the channel enhancement technique, and has the advantage…

Information Theory · Computer Science 2012-11-21 Sangwoo Park , Erchin Serpedin , Khalid Qaraqe

The quantum capacity of a noisy quantum channel determines the maximal rate at which we can code reliably over asymptotically many uses of the channel, and it characterizes the channel's ultimate ability to transmit quantum information…

Quantum Physics · Physics 2021-10-26 Xin Wang

We introduce a framework for obtaining tight mixing times for Markov chains based on what we call restricted modified log-Sobolev inequalities. Modified log-Sobolev inequalities (MLSI) quantify the rate of relative entropy contraction for…

Data Structures and Algorithms · Computer Science 2021-11-08 Nima Anari , Vishesh Jain , Frederic Koehler , Huy Tuan Pham , Thuy-Duong Vuong

We propose a new discretization of the mirror-Langevin diffusion and give a crisp proof of its convergence. Our analysis uses relative convexity/smoothness and self-concordance, ideas which originated in convex optimization, together with a…

Statistics Theory · Mathematics 2021-10-26 Kwangjun Ahn , Sinho Chewi

The use of multichannel data in line spectral estimation (or frequency estimation) is common for improving the estimation accuracy in array processing, structural health monitoring, wireless communications, and more. Recently proposed…

Information Theory · Computer Science 2018-10-15 Zai Yang , Jinhui Tang , Yonina C. Eldar , Lihua Xie

We derive improved and easily computable upper bounds on the capacity of the discrete-time Poisson channel under an average-power constraint and an arbitrary constant dark current term. This is accomplished by combining a general convex…

Information Theory · Computer Science 2020-11-03 Mahdi Cheraghchi , João Ribeiro

Approximate degradability provides a powerful framework for bounding the quantum and private capacities of noisy quantum channels in regimes where exact degradability fails. While generic low-noise channels exhibit a non-degradability…

Information Theory · Computer Science 2026-02-02 Yun-Feng Lo , Yen-Chi Lee , Min-Hsiu Hsieh

In this paper, we consider single- and multi-user Gaussian channels with feedback under expected power constraints and with non-vanishing error probabilities. In the first of two contributions, we study asymptotic expansions for the…

Information Theory · Computer Science 2016-09-22 Lan V. Truong , Silas L. Fong , Vincent Y. F. Tan

We consider the problem of distributed estimation, where local processors observe independent samples conditioned on a common random parameter of interest, map the observations to a finite number of bits, and send these bits to a remote…

Information Theory · Computer Science 2015-04-24 Aolin Xu , Maxim Raginsky

Quantum entropy inequalities are studied. Some quantum entropy inequalities are obtained by several methods. For entanglement breaking channel, we show that the entanglement-assisted classical capacity is upper bounded by $\log d$. A…

Quantum Physics · Physics 2009-11-07 Heng Fan

Noisy unsharp measurements incorporated in quantum information protocols may hinder performance, reducing the quantum advantage. However, we show that, unlike projective measurements which completely destroy quantum correlations between…

Quantum Physics · Physics 2025-07-01 Sudipta Mondal , Pritam Halder , Amit Kumar Pal , Aditi Sen De

In this paper, we present new families of quantum channels for which corresponding minimum output R\'enyi $p$-entropy is not additive. Our manuscript is motivated by the results of Grudka et al., J. Phys. A: Math. Theor. 43 425304 and we…

Quantum Physics · Physics 2025-09-08 Krzysztof Szczygielski , Michał Studziński

We consider the problem of estimating the mean of a symmetric log-concave distribution under the constraint that only a single bit per sample from this distribution is available to the estimator. We study the mean squared error as a…

Information Theory · Computer Science 2023-08-29 Alon Kipnis , John C. Duchi

We study optimal rates for quantum communication over a single use of a channel, which itself can correspond to a finite number of uses of a channel with arbitrarily correlated noise. The corresponding capacity is often referred to as the…

Quantum Physics · Physics 2010-03-19 Francesco Buscemi , Nilanjana Datta

We determine the loss in capacity incurred by using signal constellations with a bounded support over general complex-valued additive-noise channels for suitably high signal-to-noise ratio. Our expression for the capacity loss recovers the…

Information Theory · Computer Science 2016-11-17 Tobias Koch , Alfonso Martinez , Albert Guillén i Fàbregas

New upper bounds on the sum capacity of the two-user Gaussian interference channel are derived. Using these bounds, it is shown that treating interference as noise achieves the sum capacity if the interference levels are below certain…

Information Theory · Computer Science 2008-01-04 V. Sreekanth Annapureddy , Venugopal V. Veeravalli