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The R{\'e}nyi entropy is one of the important information measures that generalizes Shannon's entropy. The quantum R{\'e}nyi entropy has a fundamental role in quantum information theory, therefore, bounding this quantity is of vital…

Mathematical Physics · Physics 2016-09-26 Hadi Reisizadeh , S. Mahmoud Manjegani

In \cite{KumarS15J2}, it was shown that a generalized maximum likelihood estimation problem on a (canonical) $\alpha$-power-law model ($\mathbb{M}^{(\alpha)}$-family) can be solved by solving a system of linear equations. This was due to an…

Statistics Theory · Mathematics 2018-01-30 Atin Gayen , M. Ashok Kumar

Using arguments built on ergodicity, we derive an analytical expression for the Renyi entanglement entropies corresponding to the finite-energy density eigenstates of chaotic many-body Hamiltonians. The expression is a universal function of…

Statistical Mechanics · Physics 2019-03-12 Tsung-Cheng Lu , Tarun Grover

We consider the central limit theorem for stable laws in the case of the standardized sum of independent and identically distributed random variables with regular probability density function. By showing decay of different entropy…

Probability · Mathematics 2016-10-12 Giuseppe Toscani

Relations between Shannon entropy and Renyi entropies of integer order are discussed. For any N-point discrete probability distribution for which the Renyi entropies of order two and three are known, we provide an lower and an upper bound…

Quantum Physics · Physics 2007-05-23 Karol Zyczkowski

The Renyi entropy plays an essential role in quantum information theory. We study the continuity estimation of the Renyi entropy. An inequality relating the Renyi entropy difference of two quantum states to their trace norm distance is…

Quantum Physics · Physics 2017-01-11 Zhihua Chen , Zhihao Ma , Ismail Nikoufar , Shaoming Fei

We discuss a basic thermodynamic properties of systems with multifractal structure. This is possible by extending the notion of Gibbs-Shannon's entropy into more general framework - Renyi's information entropy. We show a connection of…

Statistical Mechanics · Physics 2009-11-07 Petr Jizba , Toshihico Arimitsu

It is possible to derive the maximum entropy principle from thermodynamic stability requirements. Using as a starting point the equilibrium probability distribution, currently used in non-extensive thermostatistics, it turns out that the…

Statistical Mechanics · Physics 2007-05-23 Jan Naudts

In this paper we extend our recent results [Physica A340 (2004)110] on q-nonextensive statistics with non-Tsallis entropies. In particular, we combine an axiomatics of Renyi with the q-deformed version of Khinchin axioms to obtain the…

Statistical Mechanics · Physics 2010-11-11 Petr Jizba , Toshihico Arimitsu

We derive the quantum Fisher information for entropy estimation in a Gibbs state and show that it equals the inverse of the heat capacity, which is dual to the temperature Fisher information given by the heat capacity divided by the square…

Quantum Physics · Physics 2026-04-08 Francis J. Headley

We present two extended forms of Fisher information that fit well in the context of nonextensive thermostatistics. We show that there exists an interplay between these generalized Fisher information, the generalized $q$-Gaussian…

Mathematical Physics · Physics 2013-06-05 Jean-François Bercher

Entropy and relative or cross entropy measures are two very fundamental concepts in information theory and are also widely used for statistical inference across disciplines. The related optimization problems, in particular the maximization…

Statistics Theory · Mathematics 2021-06-18 Abhik Ghosh , Ayanendranath Basu

We consider kinetic models for Fermi-Dirac-like particles obeying the exclusion principle. A generalized notion of Fisher information, tailored to kinetic equations of Fermi-Dirac-Fokker-Planck type, is introduced via the associated entropy…

Analysis of PDEs · Mathematics 2025-08-22 Yuzhe Zhu

Within a framework of utmost generality, we show that the entropy maximization procedure with linear constraints uniquely leads to the Shannon-Boltzmann-Gibbs entropy. Therefore, the use of this procedure with linear constraints should not…

Statistical Mechanics · Physics 2018-05-01 Thomas Oikonomou , G. Baris Bagci

Two maximization problems of R\'enyi entropy rate are investigated: the maximization over all stochastic processes whose marginals satisfy a linear constraint, and the Burg-like maximization over all stochastic processes whose…

Information Theory · Computer Science 2015-01-06 Christoph Bunte , Amos Lapidoth

Max stable laws are limit laws of linearly normalized partial maxima of indepen- dent, identically distributed (iid) random variables (rvs). These are analogous to stable laws which are limit laws of normalized partial sums of iid rvs. In…

Statistics Theory · Mathematics 2016-11-25 Sreenivasan Ravi , Ali Saeb

While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, Shannon's entropy power inequality (EPI) seems to be an exception: available information theoretic proofs of the…

Information Theory · Computer Science 2016-11-17 Olivier Rioul

We consider a bipartite quantum conductor and analyze fluctuations of heat quantity in a subsystem as well as self-information associated with the reduced-density matrix of the subsystem. By exploiting the multi-contour Keldysh technique,…

Mesoscale and Nanoscale Physics · Physics 2019-03-27 Yasuhiro Utsumi

We tighten the Entropy Power Inequality (EPI) when one of the random summands is Gaussian. Our strengthening is closely connected to the concept of strong data processing for Gaussian channels and generalizes the (vector extension of)…

Information Theory · Computer Science 2016-02-10 Thomas A. Courtade

We introduce a variant of the R\'enyi entropy definition that aligns it with the well-known H\"older mean: in the new formulation, the r-th order R\'enyi Entropy is the logarithm of the inverse of the r-th order H\"older mean. This brings…

Information Theory · Computer Science 2018-11-16 Francisco José Valverde-Albacete , Carmen Peláez-Moreno