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The Tsallis entropy, which possesses non-extensive property, is derived from the first principle employing the non-extensive Hamiltonian or the $q$-deformed Hamiltonian with the canonical ensemble assumption in statistical mechanics. Here,…

Statistical Mechanics · Physics 2025-03-11 Paradon Krisut , Sikarin Yoo-Kong

Starting from the basic prescriptions of the Tsallis' nonextensive thermostatistics, i.e. generalized entropy and normalized q-expectation values, we study the relativistic nonextensive thermodynamics and derive a Boltzmann transport…

Statistical Mechanics · Physics 2015-06-24 A. Lavagno

The Boltzmann--Gibbs entropy is a functional on the space of probability measures. When a state space is countable, one characterization of the Boltzmann--Gibbs entropy is given by the Shannon--Khinchin axioms, which consist of continuity,…

Mathematical Physics · Physics 2021-11-03 Asuka Takatsu

The Kolmogorov-Sinai entropy in the sense of Tsallis under Bernoulli shifts was obtained by Meson and Vericat [J. Math. Phys. 37, 4480(1996)]. In this paper, we propose a revised generalized Kolmogorov-Sinai-q entropy under Markov shifts.…

Chaotic Dynamics · Physics 2007-05-23 Qiang Liu , Shou-Li Peng

The Tsallis entropy given for a positive parameter $\alpha$ can be considered as a modification of the classical Shannon entropy. For the latter, corresponding to $\alpha=1$, there exist many axiomatic characterizations. One of them based…

Mathematical Physics · Physics 2017-04-27 Sonja Jäckle , Karsten Keller

A general principle called "conservation of the ellipsoid of concentration" is introduced and a generalized entropic form of order 'alpha' is optimized under this principle. It is shown that this can produce a density which can act as a…

Statistical Mechanics · Physics 2014-09-09 H. J. Haubold , A. M. Mathai , S. Thomas

The nonextensive statistics based on Tsallis entropy have been so far used for the systems composed of subsystems having same $q$. The applicability of this statistics to the systems with different $q$'s is still a matter of investigation.…

Statistical Mechanics · Physics 2007-05-23 Qiuping A. Wang

In this paper we introduce a nonextensive quantum information theoretic measure which may be defined between any arbitrary number of density matrices, and we analyze its fundamental properties in the spectral graph-theoretic framework.…

Information Theory · Computer Science 2015-04-15 A. Ben Hamza

Tsallis has proposed a generalization of Boltzmann-Gibbs thermostatistics by introducing a family of generalized nonextensive entropy functionals with a single parameter $q$. These reduce to the extensive Boltzmann-Gibbs form for $q=1$, but…

Statistical Mechanics · Physics 2007-05-23 Bruce M. Boghosian

We revisit the derivation of a formula for the $q$-generalised multinomial coefficient rooted in the $q$-deformed algebra, a foundational framework in the study of nonextensive statistics. Previous approximate expressions in the literature…

Statistical Mechanics · Physics 2024-10-08 Keisuke Okamura

The purpose of this note is to argue that degree of nonextensivity as given by Tsallis distribution obtained from maximum entropy principle has a different origin than nonextensivity inferred from pseudo-additive property of Tsallis…

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

Fundamental properties for the Tsallis relative entropy in both classical and quantum systems are studied. As one of our main results, we give the parametric extension of the trace inequality between the quantum relative entropy and the…

Statistical Mechanics · Physics 2016-08-31 S. Furuichi , K. Yanagi , K. Kuriyama

We define an entropy based on a chosen governing probability distribution. If a certain kind of measurements follow such a distribution it also gives us a suitable scale to study it with. This scale will appear as a link function that is…

Data Analysis, Statistics and Probability · Physics 2007-10-24 Peter Sunehag

A method of estimating the joint probability mass function of a pair of discrete random variables is described. This estimator is used to construct the conditional Shannon-R\'eyni-Tsallis entropies estimates. From there almost sure rates of…

Statistics Theory · Mathematics 2020-02-18 Ba Amadou Diadie , Lo Gane Samb

This article extends the non-extensive entropy of Tsallis and uses this entropy to model an energy producing system in an absorbing heat bath. This modified non-extensive entropy is superficially identical to the one proposed by Tsallis,…

Statistical Mechanics · Physics 2007-05-23 Mark Fleischer

Tsallis entropy is a useful one-parameter generalization of the standard von Neumann entropy in information theory. We study the variance of Tsallis entropy of bipartite quantum systems in a random pure state. The main result is an exact…

Mathematical Physics · Physics 2022-02-16 Lu Wei

Recently, a new measure of information called extropy has been introduced by Lad, Sanfilippo and Agr\`o as the dual version of Shannon entropy. In the literature, Tsallis introduced a measure for a discrete random variable, named Tsallis…

Probability · Mathematics 2021-09-30 Narayanaswamy Balakrishnan , Francesco Buono , Maria Longobardi

We expand the Tsallis distribution in a Taylor series of powers of (q-1), where q is the Tsallis parameter, assuming q is very close to 1. This helps in studying the degree of deviation of transverse momentum spectra and other thermodynamic…

High Energy Physics - Phenomenology · Physics 2016-02-23 Trambak Bhattacharyya , Jean Cleymans , Arvind Khuntia , Pooja Pareek , Raghunath Sahoo

In this short paper, we establish a variational expression of the Tsallis relative entropy. In addition, we derive a generalized thermodynamic inequality and a generalized Peierls-Bogoliubov inequality. Finally we give a generalized…

Statistical Mechanics · Physics 2010-01-10 Shigeru Furuichi

In this paper, we propose a new discriminative model named \emph{nonextensive information theoretical machine (NITM)} based on nonextensive generalization of Shannon information theory. In NITM, weight parameters are treated as random…

Machine Learning · Computer Science 2016-04-22 Chaobing Song , Shu-Tao Xia