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Related papers: MAXENT and the Tsallis Parameter

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We develop a method using a coarse graining of the energy fluctuations of an equilibrium quantum system which produces simple parameterizations for the behaviour of the system. As an application, we use these methods to gain more…

Statistical Mechanics · Physics 2007-05-23 Jani Lukkarinen

We apply non-extensive methods to the statistical analysis of fully developed turbulent flows. Probability density functions of velocity differences at distance r obtained by extremizing the Tsallis entropies coincide well with what is…

Statistical Mechanics · Physics 2007-05-23 Christian Beck

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

We present a path toward determining the statistical origin of the thermodynamic limit for systems with long-range interactions. We assume throughout that the systems under consideration have thermodynamic properties given by the Tsallis…

Statistical Mechanics · Physics 2015-06-18 Nikos Kalogeropoulos

Self-gravitating systems are generally thought to behavior non-extensively due to the long-range nature of gravitational forces. We obtain a relation between the nonextensive parameter q of Tsallis statistics, the temperature gradient and…

Astrophysics · Physics 2015-08-10 Jiulin Du

It is shown that the R\'enyi and Tsallis entropies and the q-expectation values, are continuous and stable if $q>1$ and are not continuous and instable for uniform finite distributions if $q<1$.

Statistical Mechanics · Physics 2009-10-13 T. Matolcsi , P. Ván

In this paper we give an interpretation of Tsallis' nonextensive statistical mechanics based upon the information-theoretic point of view of Luzzi et al. [cond-mat/0306217; cond-mat/0306247; cond-mat/0307325], suggesting Tsallis' entropy to…

Statistical Mechanics · Physics 2015-06-24 F. Sattin

This paper studies the continuous-time reinforcement learning in jump-diffusion models by featuring the q-learning (the continuous-time counterpart of Q-learning) under Tsallis entropy regularization. Contrary to the Shannon entropy, the…

Optimization and Control · Mathematics 2026-02-16 Lijun Bo , Yijie Huang , Xiang Yu , Tingting Zhang

The local structure entropy is a new method which is proposed to identify the influential nodes in the complex networks. In this paper a new form of the local structure entropy of the complex networks is proposed based on the Tsallis…

Social and Information Networks · Computer Science 2015-02-03 Qi Zhang , Meizhu Li , Yuxian Du , Yong Deng , Sankaran Mahadevan

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

We extend the Hanel and Thurner asymptotic analysis to both extensive and non-extensive entropies on the basis of a wide class of entropic forms. The procedure is known to be capable to classify multiple entropy measures in terms of their…

Statistical Mechanics · Physics 2020-02-21 Nana Cabo Bizet , Jesus Fuentes , Octavio Obregon

The q-exponential distributions, which are generalizations of the Zipf-Mandelbrot power-law distribution, are frequently encountered in complex systems at their stationary states. From the viewpoint of the principle of maximum entropy, they…

Statistical Mechanics · Physics 2009-11-07 Sumiyoshi Abe

We consider a family of quantum conditional entropies based on the concept of quantum $f$-divergences. First, we explicitly formulate conditions under which the notion of quantum conditional entropy is well defined in this way. In…

Quantum Physics · Physics 2015-06-17 Alexey E. Rastegin

There are numerous characterizations of Shannon entropy and Tsallis entropy as measures of information obeying certain properties. Using work by Faddeev and Furuichi, we derive a very simple characterization. Instead of focusing on the…

Information Theory · Computer Science 2017-08-22 John C. Baez , Tobias Fritz , Tom Leinster

Symbolic sequences with long-range correlations are expected to result in a slow regression to a steady state of entropy increase. However, we prove that also in this case a fast transition to a constant rate of entropy increase can be…

chao-dyn · Physics 2015-06-24 Marco Buiatti , Paolo Grigolini , Luigi Palatella

We determine a general link between two different solutions of the MaxEnt variational problem, namely, the ones that correspond to using either Shannon's or Tsallis' entropies in the concomitant variational problem. It is shown that the two…

Statistics Theory · Mathematics 2015-06-03 E. Rufeil Fiori , A. Plastino

Ill-posed inverse problems of the form y = X p where y is J-dimensional vector of a data, p is m-dimensional probability vector which cannot be measured directly and matrix X of observable variables is a known J,m matrix, J < m, are…

Mathematical Physics · Physics 2012-08-27 M. Grendar, , M. Grendar

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

An updated review [1] of nonextensive statistical mechanics and thermodynamics is colloquially presented. Quite naturally the possibility emerges for using the value of q-1 (entropic nonextensivity) as a simple and efficient manner to…

Statistical Mechanics · Physics 2007-05-23 Constantino Tsallis

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It…

Computation · Statistics 2023-05-19 Viktor Witkovský