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Related papers: The q-exponential family in statistical physics

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We discuss the possibility of using generalized canonical distributions, i.e. using other factors than $\exp(-\beta E)$, in order to compute the equilibrium properties of physical systems. It will be show that some other choices can, in…

Statistical Mechanics · Physics 2007-05-23 Raul Toral

A generalized definition of average, termed the q-average, is widely employed in the field of nonextensive statistical mechanics. Recently, it has however been pointed out that such an average value may behave unphysical under specific…

Statistical Mechanics · Physics 2011-09-09 Sumiyoshi Abe

We address the problem of learning of continuous exponential family distributions with unbounded support. While a lot of progress has been made on learning of Gaussian graphical models, we still lack scalable algorithms for reconstructing…

Machine Learning · Computer Science 2022-03-01 Christopher X. Ren , Sidhant Misra , Marc Vuffray , Andrey Y. Lokhov

From a new class of q-deformed coherent states we introduce a generalization of the Euler probability distribution for which the main statistical parameters are obtained explicitly. As application, we discuss the corresponding photon…

Mathematical Physics · Physics 2021-07-14 Zouhair Mouayn , Othmane El moize

The original canonical ensemble formalism for the nonextensive entropy thermostatistics is reconsidered. It is shown that the unambiguous connection of the statistical mechanics with the equilibrium thermodynamics is provided if the…

Statistical Mechanics · Physics 2009-11-11 A. S. Parvan

Many statistical models are algebraic in that they are defined in terms of polynomial constraints, or in terms of polynomial or rational parametrizations. The parameter spaces of such models are typically semi-algebraic subsets of the…

Statistics Theory · Mathematics 2010-03-04 Mathias Drton , Seth Sullivant

The (general) hypoexponential distribution is the distribution of a sum of independent exponential random variables. We consider the particular case when the involved exponential variables have distinct rate parameters. We prove that the…

Probability · Mathematics 2020-12-16 George P. Yanev

It is shown by simple and straightforward considerations that discreteness of basic physical variables is, at least, essential for generalized statistical mechanics with non-logarithmic entropy to be thermodynamically applicable to…

Statistical Mechanics · Physics 2015-05-19 Sumiyoshi Abe

We introduce a new definition of exponential family of Markov chains, and show that many characteristic properties of the usual exponential family of probability distributions are properly extended to Markov chains. The method of…

Information Theory · Computer Science 2017-01-24 Hiroshi Nagaoka

We study generalizations of It\^{o}-Langevin dynamics consistent within nonextensive thermostatistics. The corresponding stochastic differential equations are shown to be connected with a wide class of nonlinear Fokker-Planck equations…

Statistical Mechanics · Physics 2022-07-14 Leonardo Santos

The statistical mechanics of a cloud of particles interacting via their gravitational potentials is an old problem which encounters some issues when the traditional Boltzmann-Gibbs statistics is applied. In this article, we consider the…

Statistical Mechanics · Physics 2018-04-10 Lenin Escamilla-Herrera , Christine Gruber , Viridiana Pineda , Hernando Quevedo

In this note we establish simple and verifiable analytical conditions for a power series f in the class K, and its associated Khinchin family, to be Gaussian. We give several moment criteria for general power series with non-negative…

Probability · Mathematics 2025-01-17 Víctor J. Maciá

We show, on purely statistical grounds and without appeal to any physical model, that a power-law $q-$entropy $S_q$, with $0<q<1$, can be {\it extensive}. More specifically, if the components $X_i$ of a vector $X \in \mathbb{R}^N$ are…

Statistical Mechanics · Physics 2009-11-11 C. Vignat , A. Plastino , A. R. Plastino

Quasi-power law ensembles are discussed from the perspective of nonextensive Tsallis distributions characterized by a nonextensive parameter $q$. A number of possible sources of such distributions are presented in more detail. It is further…

Statistical Mechanics · Physics 2023-07-19 Grzegorz Wilk , Zbigniew Włodarczyk

An essential prerequisite for the study of q-deformed physics are particle states in position and momentum representation. In order to relate x- and p-space by Fourier transformations the appropriate q-exponential series related to…

High Energy Physics - Theory · Physics 2009-10-28 Arne Schirrmacher

In this present work, we discuss the Bayesian inference for the bivariate pseudo-exponential distribution. Initially, we assume independent gamma priors and then pseudo-gamma priors for the pseudo-exponential parameters. We are primarily…

Methodology · Statistics 2023-06-27 Banoth Veeranna

The critique against using Boltzmann's microcanonical entropy, an "ensemble measure", as foundation of statistics is rebuffed. The confusion of the microcanonical distribution with the exponential Boltzmann-Gibbs (``BG'') distribution is…

Statistical Mechanics · Physics 2007-05-23 D. H. E. Gross

This work studies the large sample properties of the posterior-based inference in the curved exponential family under increasing dimension. The curved structure arises from the imposition of various restrictions on the model, such as moment…

Statistics Theory · Mathematics 2017-10-05 Alexandre Belloni , Victor Chernozhukov

Fractional $q$-extensions of some classical $q$-orthogonal polynomials are introduced and some of the main properties of the new defined functions are given. Next, a fractional $q$-difference equation of Gauss type is introduced and solved…

Classical Analysis and ODEs · Mathematics 2016-12-28 P. Njionou Sadjang , S. Mboutngam

Diffusion processes are a class of stochastic differential equations (SDEs) providing a rich family of expressive models that arise naturally in dynamic modelling tasks. Probabilistic inference and learning under generative models with…

Machine Learning · Computer Science 2024-02-28 Prakhar Verma , Vincent Adam , Arno Solin
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