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The relative entropy of entanglement $E_R$ is defined as the distance of a multi-partite quantum state from the set of separable states as measured by the quantum relative entropy. We show that this optimisation is always achieved, i.e. any…

Quantum Physics · Physics 2023-10-27 Ludovico Lami , Maksim E. Shirokov

In the framework of the Tsallis statistical mechanics, for the spin-1/2 and the harmonic oscillator, we study the change of the population of states when the parameter $q$ is varied; the results show that the difference between predictions…

Statistical Mechanics · Physics 2010-11-17 Ali M. Nassimi , Gholamabbas Parsafar

The thermodynamic stability condition (TSC) of Tsallis' entropy is revisited. As Ramshaw [Phys. Lett. A {\bf 198} (1995) 119] has already pointed out, the concavity of Tsallis' entropy with respect to the internal energy is not sufficient…

Statistical Mechanics · Physics 2009-11-07 T. Wada

Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative…

Artificial Intelligence · Computer Science 2009-11-10 Ali E. Abbas

Algorithmic entropy and Shannon entropy are two conceptually different information measures, as the former is based on size of programs and the later in probability distributions. However, it is known that, for any recursive probability…

Information Theory · Computer Science 2010-06-03 Andreia Teixeira , Andre Souto , Armando Matos , Luis Antunes

A statistical thermodynamic approach of moving particles forming an elastic body is presented which leads to reveal molecular-mechanical properties of classical and nonextensive dynamical systems. We derive the Boltzmann-Gibbs (BG) entropy…

Statistical Mechanics · Physics 2009-11-10 Enrique Canessa

Bayes' theorem incorporates distinct types of information through the likelihood and prior. Direct observations of state variables enter the likelihood and modify posterior probabilities through consistent updating. Information in terms of…

Methodology · Statistics 2024-07-19 Duncan K. Foley , Ellis Scharfenaker

The Renyi entropy with a free Renyi parameter $q$ is the most justified form of information entropy, and the Tsallis entropy may be regarded as a linear approximation to the Renyi entropy when $q\simeq 1$. When $q\to 1$, both entropies go…

Statistical Mechanics · Physics 2007-05-23 Andrei G. Bashkirov

In this work, we derive information-theoretic properties for a modified Tsallis entropy, hereinafter referred to as q-entropy. We introduce the notions of joint q-entropy, conditional q-entropy, relative q-entropy, conditional mutual…

Mathematical Physics · Physics 2026-03-31 Marco A. S. Trindade

The maximum entropy principle in Tsallis statistics is reformulated in the mathematical framework of the q-product, which results in the unique non self-referential q-canonical distribution. As one of the applications of the present…

Statistical Mechanics · Physics 2009-11-11 Hiroki Suyari

We formulate some properties of a set of several mutually unbiased measurements. These properties are used for deriving entropic uncertainty relations. Applications of mutually unbiased measurements in entanglement detection are also…

Quantum Physics · Physics 2015-05-07 Alexey E. Rastegin

The pathway model of Mathai (2005) is shown to be inferable from the maximization of a certain generalized entropy measure. This entropy is a variant of the generalized entropy of order 'alpha', considered in Mathai and Rathie (1975), and…

Statistical Mechanics · Physics 2009-11-11 A. M. Mathai , H. J. Haubold

In many applications, the probability density function is subject to experimental errors. In this work the continuos dependence of a class of generalized entropies on the experimental errors is studied. This class includes the C. Shannon,…

Data Analysis, Statistics and Probability · Physics 2016-05-20 György Steinbrecher , Giorgio Sonnino

For the generalized statistical mechanics based on the Tsallis entropy, a variational perturbation approximation method with the principle of minimal sensitivity is developed by calculating the generalized free energy up to the third order…

Statistical Mechanics · Physics 2007-05-23 Wen-Fa Lu

We show that starting with either the non-extensive Tsallis entropy in Wang's formalism or the extensive Renyi entropy, it is possible to construct the equilibrium statistical mechanics with non-Gibbs canonical distribution functions. The…

High Energy Physics - Phenomenology · Physics 2009-11-10 A. S. Parvan , T. S. Biro

We study the continuity property of the generalized entropy as a function of the underlying probability distribution, defined with an action space and a loss function, and use this property to answer the basic questions in statistical…

Machine Learning · Computer Science 2022-01-04 Aolin Xu

Recently, Gross claims that Boltzmann entropy $S=k\ln W$ is valid for any system at equilibrium, so that Tsallis entropy is useless in this case. I comment on some arguments forwarded to reach this conclusion and argue that the additive…

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

A comparative study of one-dimensional quantum structures which allow analytic expressions for the position and momentum R\'{e}nyi $R(\alpha)$ and Tsallis $T(\alpha)$ entropies, focuses on extracting the most characteristic physical…

Quantum Physics · Physics 2019-01-15 O. Olendski

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

We review with a tutorial scope the information theory foundations of quantum statistical physics. Only a small proportion of the variables that characterize a system at the microscopic scale can be controlled, for both practical and…

Statistical Mechanics · Physics 2007-05-23 R. Balian
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