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We develop a maximum relative entropy formalism to generate optimal approximations to probability distributions. The central results consist in (a) justifying the use of relative entropy as the uniquely natural criterion to select a…

Statistical Mechanics · Physics 2008-10-17 Chih-Yuan Tseng , Ariel Caticha

Traditionally, the Method of (Shannon-Kullback's) Relative Entropy Maximization (REM) is considered with linear moment constraints. In this work, the method is studied under frequency moment constraints which are non-linear in…

Data Analysis, Statistics and Probability · Physics 2012-08-27 M. Grendar, , M. Grendar

This paper considers an information bottleneck problem with the objective of obtaining a most informative representation of a hidden feature subject to a R\'enyi entropy complexity constraint. The optimal bottleneck trade-off between…

Information Theory · Computer Science 2021-02-01 Jian-Jia Weng , Fady Alajaji , Tamás Linder

Data partitioning that maximizes/minimizes the Shannon entropy, or more generally the R\'enyi entropy is a crucial subroutine in data compression, columnar storage, and cardinality estimation algorithms. These partition algorithms can be…

Data Structures and Algorithms · Computer Science 2025-11-05 Aryan Esmailpour , Sanjay Krishnan , Stavros Sintos

We present a universal relation between the flow of a Renyi entropy and the full counting statistics of energy transfers. We prove the exact relation for a flow to a system in thermal equilibrium that is weakly coupled to an arbitrary…

Quantum Physics · Physics 2015-06-02 Mohammad H. Ansari , Yuli V. Nazarov

Many complex systems are characterized by non-Boltzmann distribution functions of their statistical variables. If one wants to -- justified or not -- hold on to the maximum entropy principle for complex statistical systems (non-Boltzmann)…

Statistical Mechanics · Physics 2009-11-13 Stefan Thurner , Rudolf Hanel

We obtain formulas for Petz-R\'enyi and Umegaki relative entropy from the idea of distribution of a positive selfadjoint operator. Classical results on R\'enyi and Kullback-Leibler divergences are applied to obtain new results and new…

Quantum Physics · Physics 2023-08-15 George Androulakis , Tiju Cherian John

We prove a quantitative dimension-free bound in the Shannon-Stam Entropy inequality for the convolution of two log-concave distributions in dimension d interms of the spectral gap of the density. The method relies on the analysis of the…

Functional Analysis · Mathematics 2013-06-04 Keith Ball , Van Hoang Nguyen

R\'enyi entropy is a one-parameter generalization of Shannon entropy, which has been used in various fields of physics. Despite its wide applicability, the physical interpretations of the R\'enyi entropy are not widely known. In this paper,…

Statistical Mechanics · Physics 2024-08-29 Misaki Ozawa , Nina Javerzat

We consider 3d N>= 2 superconformal field theories on a branched covering of a three-sphere. The Renyi entropy of a CFT is given by the partition function on this space, but conical singularities break the supersymmetry preserved in the…

High Energy Physics - Theory · Physics 2015-06-16 Tatsuma Nishioka , Itamar Yaakov

In this study an attempt has been made to propose a way to develop new distribution. For this purpose, we need only idea about distribution function. Some important statistical properties of the new distribution like moments, cumulants,…

Methodology · Statistics 2024-08-30 Brijesh P. Singh , Utpal Dhar Das

A framework for deriving R\'enyi entropy-power inequalities (EPIs) is presented that uses linearization and an inequality of Dembo, Cover, and Thomas. Simple arguments are given to recover the previously known R\'enyi EPIs and derive new…

Information Theory · Computer Science 2020-04-08 Olivier Rioul

By replacing linear averaging in Shannon entropy with Kolmogorov-Nagumo average (KN-averages) or quasilinear mean and further imposing the additivity constraint, R\'{e}nyi proposed the first formal generalization of Shannon entropy. Using…

Information Theory · Computer Science 2007-07-13 Ambedkar Dukkipati , M. Narasimha Murty , Shalabh Bhatnagar

Maximum entropy principle does not seem to distinguish between the use of Tsallis and Renyi entropies as either of them may be used to derive similar power-law distributions. In this paper, we address the question whether the Renyi entropy…

Statistical Mechanics · Physics 2007-05-23 Ramandeep S. Johal , Ugur Tirnakli

We developed a perturbative calculation for entropy dynamics considering a sudden coupling between a system and a bath. The theory we developed can work in general environment without Markovian approximation. A perturbative formula is given…

High Energy Physics - Theory · Physics 2021-05-12 Yu Chen

The thermodynamic maximum principle for the Boltzmann-Gibbs-Shannon (BGS) entropy is reconsidered by combining elements from group and measure theory. Our analysis starts by noting that the BGS entropy is a special case of relative entropy.…

Statistical Mechanics · Physics 2008-11-26 Jörn Dunkel , Peter Talkner , Peter Hänggi

An amended MaxEnt formulation for systems displaced from the conventional MaxEnt equilibrium is proposed. This formulation involves the minimization of the Kullback-Leibler divergence to a reference $Q$ (or maximization of Shannon…

Mathematical Physics · Physics 2009-11-11 Jean-François Bercher

In the world of generalized entropies---which, for example, play a role in physical systems with sub- and super-exponential phasespace growth per degree of freedom---there are two ways for implementing constraints in the maximum entropy…

Mathematical Physics · Physics 2019-02-20 Jan Korbel , Rudolf Hanel , Stefan Thurner

We show how convergence to the Gumbel distribution in an extreme value setting can be understood in an information-theoretic sense. We introduce a new type of score function which behaves well under the maximum operation, and which implies…

Statistics Theory · Mathematics 2024-07-22 Oliver Johnson

There are no universally accepted definitions of R\'enyi conditional entropy and R\'enyi mutual information, although motivated by different applications, several definitions have been proposed in the literature. In this paper, we consider…

Information Theory · Computer Science 2025-11-05 Shi-Bing Li , Ke Li , Lei Yu