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Quite general, analytical (both exact and approximate) forms for discrete probability distributions (PD's) that maximize Tsallis entropy for a fixed variance are here investigated. They apply, for instance, in a wide variety of scenarios in…

Statistical Mechanics · Physics 2009-11-11 C. Vignat , A. Plastino

The rate-distortion-perception function (RDPF; Blau and Michaeli, 2019) has emerged as a useful tool for thinking about realism and distortion of reconstructions in lossy compression. Unlike the rate-distortion function, however, it is…

Information Theory · Computer Science 2021-04-29 Lucas Theis , Aaron B. Wagner

A unified presentation of the perturbation and variational methods for the generalized statistical mechanics based on Tsallis entropy is given here. In the case of the variational method, the Bogoliubov inequality is generalized in a very…

Statistical Mechanics · Physics 2009-10-31 E. K. Lenzi , L. C. Malacarne , R. S. Mendes

We study the compression of data in the case where the useful information is contained in a set rather than a vector, i.e., the ordering of the data points is irrelevant and the number of data points is unknown. Our analysis is based on…

Information Theory · Computer Science 2018-05-23 Günther Koliander , Dominic Schuhmacher , Franz Hlawatsch

The nonextensitivity parameter $q$ occuring in some of the applications of Tsallis statistics (known also as index of the corresponding L\'evy distribution) is shown to be given, in $q>1$ case, entirely by the fluctuations of the parameters…

High Energy Physics - Phenomenology · Physics 2011-05-05 G. Wilk , Z. Wlodarczyk

Within the Tsallis thermodynamics' framework, and using scaling properties of the entropy, we derive a generalization of the Gibbs-Duhem equation. The analysis suggests a transformation of variables that allows standard thermodynamics to be…

Statistical Mechanics · Physics 2009-11-07 Eduard Vives , Antoni Planes

Since Shannon's foundational work, rate-distortion theory has defined the fundamental limits of lossy compression. Classical results, derived for memoryless and stationary ergodic sources in the asymptotic regime, have shaped both transform…

Information Theory · Computer Science 2026-03-11 Sujata Sinha , Vishwas Rao , Robert Underwood , David Lenz , Sheng Di , Franck Cappello , Lingjia Liu

Consider the problem where a statistician in a two-node system receives rate-limited information from a transmitter about marginal observations of a memoryless process generated from two possible distributions. Using its own observations,…

Information Theory · Computer Science 2017-03-02 Gil Katz , Pablo Piantanida , Mérouane Debbah

We apply Tsallis's q-indexed entropy to formulate a non-extensive random matrix theory (RMT), which may be suitable for systems with mixed regular-chaotic dynamics. The joint distribution of the matrix elements is given by folding the…

Statistical Mechanics · Physics 2007-05-23 A. Y. Abul-Magd

This paper studies the fundamental limits of the minimum average length of lossless and lossy variable-length compression, allowing a nonzero error probability $\epsilon$, for lossless compression. We give non-asymptotic bounds on the…

Information Theory · Computer Science 2015-10-09 Victoria Kostina , Yury Polyanskiy , Sergio Verdú

The nuclear modification factor is derived using Tsallis non-extensive statistics in relaxation time approximation. The variation of nuclear modification factor with transverse momentum for different values of non-extensive parameter, $q$,…

Introducing the generalized, non-extensive statistics proposed by Tsallis[1988], into the standard s-wave pairing BCS theory of superconductivity in 2D yields a reasonable description of many of the main properties of high temperature…

Superconductivity · Physics 2009-11-07 H. Uys , H. G. Miller , F. C. Khanna

A framework is developed using techniques from rate distortion theory in statistical testing. The idea is first to do optimal compression according to a certain distortion function and then use information divergence from the compressed…

Information Theory · Computer Science 2009-04-01 Peter Harremoes

The current status of implementing Tsallis (nonextensive) statistics on high-energy physics is briefly reviewed. The remarkably low freezeout-temperature, which apparently fails to reproduce the first-principle lattice QCD thermodynamics…

High Energy Physics - Phenomenology · Physics 2018-04-30 Abdel Nasser Tawfik

In many situations, in all branches of physics, one encounters power-like behavior of some variables which are best described by a Tsallis distribution characterized by a nonextensivity parameter $q$ and scale parameter $T$. However, there…

Statistical Mechanics · Physics 2015-01-16 Grzegorz Wilk , Zbigniew Wlodarczyk

This paper investigates the rate-distortion function, under a squared error distortion $D$, for an $n$-dimensional random vector uniformly distributed on an $(n-1)$-sphere of radius $R$. First, an expression for the rate-distortion function…

Information Theory · Computer Science 2024-01-10 Alex Dytso , Martina Cardone

We examine the coordinated and universal rate-efficient sampling of a subset of correlated discrete memoryless sources followed by lossy compression of the sampled sources. The goal is to reconstruct a predesignated subset of sources within…

Information Theory · Computer Science 2017-06-23 Vinay Praneeth Boda , Prakash Narayan

Recent progresses in statistical mechanics indicate the Tsallis nonextensive thermostatistics as the natural generalization of the standard classical and quantum statistics, when memory effects and long-range forces are not negligible. In…

Nuclear Theory · Physics 2007-05-23 G. Kaniadakis , A. Lavagno , M. Lissia , P. Quarati

We consider finite blocklength lossy compression of information sources whose components are independent but non-identically distributed. Crucially, Gaussian sources with memory and quadratic distortion can be cast in this form. We show…

Information Theory · Computer Science 2026-02-11 Eyyup Tasci , Victoria Kostina

The rate-distortion dimension (RDD) of an analog stationary process is studied as a measure of complexity that captures the amount of information contained in the process. It is shown that the RDD of a process, defined as two times the…

Information Theory · Computer Science 2016-11-18 Farideh Ebrahim Rezagah , Shirin Jalali , Elza Erkip , H. Vincent Poor