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We show that within classical statistical mechanics it is possible to naturally derive power law distributions which are of Tsallis type. The only assumption is that microcanonical distributions have to be separable from of the total system…

Statistical Mechanics · Physics 2009-11-10 Rudolf Hanel , Stefan Thurner

To know the statistical distribution of a variable is an important problem in management of resources. Distributions of the power law type are observed in many real systems. However power law distributions have an infinite variance and thus…

Statistical Mechanics · Physics 2008-12-02 Hari M. Gupta , Jose R. Campanha

The asymptotic correspondence between the probability mass function of the $q$-deformed multinomial distribution and the $q$-generalised Kullback-Leibler divergence, also known as Tsallis relative entropy, is established. The probability…

Statistical Mechanics · Physics 2025-03-10 Keisuke Okamura

Gauss' law of error is generalized in Tsallis statistics such as multifractal systems, in which Tsallis entropy plays an essential role instead of Shannon entropy. For the generalization, we apply the new multiplication operation determined…

Statistical Mechanics · Physics 2007-05-23 Hiroki Suyari , Makoto Tsukada

The Large Deviation Principle (LDP) and the Central Limit Theorem (CLT) are central pillars of probability theory. While their formulations are established under the i.i.d. assumption, the probabilistic foundation for power-law…

Probability · Mathematics 2026-04-22 Hiroki Suyari , Antonio M. Scarfone

We show that size-rank distributions with power-law decay (often only over a limited extent) observed in a vast number of instances in a widespread family of systems obey Tsallis statistics. The theoretical framework for these distributions…

Statistical Mechanics · Physics 2014-09-29 G. Cigdem Yalcin , Alberto Robledo , Murray Gell-Mann

There exist two different versions of the Kullback-Leibler divergence (K-Ld) in Tsallis statistics, namely the usual generalized K-Ld and the generalized Bregman K-Ld. Problems have been encountered in trying to reconcile them. A condition…

Statistical Mechanics · Physics 2015-05-27 R. C. Venkatesan , A. Plastino

The equipartition theorem states that inverse temperature equals the log-derivative of the density of states. This relation can be generalized by introducing a proportionality factor involving an increasing positive function phi(x). It is…

Statistical Mechanics · Physics 2009-11-10 Jan Naudts

The generalized Kullback-Leibler divergence (K-Ld) in Tsallis statistics [constrained by the additive duality of generalized statistics (dual generalized K-Ld)] is here reconciled with the theory of Bregman divergences for expectations…

Statistical Mechanics · Physics 2015-05-27 R. C. Venkatesan , A. Plastino

We show that within classical statistical mechanics without taking the thermodynamic limit, the most general Boltzmann factor for the canonical ensemble is a q-exponential function. The only assumption here is that microcanonical…

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

From the Tsallis unnormalized (or Tsallis-2) statistical mechanical formulation, B\"{u}y\"{u}kkili\c{c} {\it et al.} [Phys. Lett. A 197, 209 (1995)] derived the expressions for the single-particle distribution functions (known as the…

Statistical Mechanics · Physics 2021-12-09 A. S. Parvan , T. Bhattacharyya

In the present article the author extends the Fourier transform to a more general class of functions; First to power-law functions with integer and half-integer exponents then to the widely used quantum statistics function (Fermi-Dirac and…

General Mathematics · Mathematics 2019-12-30 Cyril Belardinelli

We present the q-Stirling's formula using the q-product determined by Tsallis entropy as nonextensive generalization of the usual Stirling's formula. The numerical computations and the proof are also shown. Moreover, we derive and prove…

Statistical Mechanics · Physics 2007-05-23 Hiroki Suyari

In the present work, we have found that the phenomenological Tsallis distribution (which nowadays is largely used to describe the transverse momentum distributions of hadrons measured in $pp$ collisions at high energies) is consistent with…

Nuclear Theory · Physics 2021-12-09 A. S. Parvan

The paper considers the problem of calculating the distribution function of a strictly stable law at $x\to\infty$. To solve this problem, an expansion of the distribution function in a power series was obtained, and an estimate of the…

Statistics Theory · Mathematics 2023-03-23 Viacheslav V. Saenko

The Weibull distribution can be obtained using a power transformation from the standard exponential distribution. In this article, we will consider a symmetrized power transformation of a random variable with the standard normal…

Probability · Mathematics 2024-01-09 Krzysztof Zajkowski

We derive a scaling property from a fundamental nonlinear differential equation whose solution is the so-called q-exponential function. A scaling property has been believed to be given by a power function only, but actually more general…

Statistical Mechanics · Physics 2007-05-23 Hiroki Suyari , Tatsuaki Wada

We perform a Taylor series expansion of Tsallis distribution by assuming the Tsallis parameter $q$ close to 1. The $q$ value shows the deviation of a system from a thermalised Boltzmann distribution. By taking up to first order in $(q-1)$,…

High Energy Physics - Phenomenology · Physics 2016-03-17 Trambak Bhattacharyya , Arvind Khuntia , Pragati Sahoo , Prakhar Garg , Pooja Pareek , Raghunath Sahoo , Jean Cleymans

We find the value of constants related to constraints in characterization of some known statistical distributions and then we proceed to use the idea behind maximum entropy principle to derive generalized version of this distributions using…

Statistical Mechanics · Physics 2007-05-23 Oscar Sotolongo-Costa , Alejandro Gonzalez Gonzalez , Francois Brouers

Many policy optimization approaches in reinforcement learning incorporate a Kullback-Leilbler (KL) divergence to the previous policy, to prevent the policy from changing too quickly. This idea was initially proposed in a seminal paper on…

Machine Learning · Computer Science 2024-03-19 Lingwei Zhu , Zheng Chen , Matthew Schlegel , Martha White
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