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Large real-life complex networks are often modeled by various random graph constructions and hundreds of further references therein. In many cases it is not at all clear how the modeling strength of differently generated random graph model…

Data Structures and Algorithms · Computer Science 2020-09-01 András Faragó , Rupei Xu

Statistical formulations of thermodynamic entropy, such as those by Boltzmann and Gibbs, were originally developed for classical systems and are well understood in that context. However, the foundational aspects of quantum statistical…

Quantum Physics · Physics 2025-10-08 Smitarani Mishra , Shaon Sahoo

The cornerstones of Boltzmann-Gibbs and nonextensive statistical mechanics respectively are the entropies $S_{BG} \equiv -k \sum_{i=1}^W p_i \ln p_i $ and $S_{q}\equiv k (1-\sum_{i=1}^Wp_i^{q})/(q-1) (q\in{\mathbb R} ; S_1=S_{BG})$. Through…

Statistical Mechanics · Physics 2017-08-23 Constantino Tsallis

The properties of the nonextensive parameter q and the Tsallis distribution for self-gravitating systems are studied. A mathematical expression of q is deduced based on the generalized Boltzmann equation, the q-H theorem and the generalized…

Statistical Mechanics · Physics 2015-08-10 Jiulin Du

We study the consequences of introducing quantum group invariance in the formalism of nonextensive quantum statistical mechanics. We find that the corresponding thermodynamical system is equivalent to a Bose-Einstein gas in the…

Condensed Matter · Physics 2016-08-31 Marcelo R. Ubriaco

Starting from an important research path, we consider gravity as a collective phenomenon governed by statistical mechanics. While previous studies have focussed on the thermodynamic heat flow across a 2d-horizon as perceived by a single,…

General Relativity and Quantum Cosmology · Physics 2018-04-12 Pierre A Mandrin

This paper applies the formalism of classical, Gibbs-Boltzmann statistical mechanics to the phenomenon of non-thermal damage. As an example, a non-thermal fiber-bundle model with the global uniform (meanfield) load sharing is considered.…

Statistical Mechanics · Physics 2008-10-01 S. G. Abaimov

It is notoriously difficult to apply statistical mechanics to generally covariant systems, because the notions of time, energy and equilibrium are seriously modified in this context. We discuss the conditions under which weaker versions of…

General Relativity and Quantum Cosmology · Physics 2016-06-15 Goffredo Chirco , Thibaut Josset , Carlo Rovelli

The basic aspects of both Boltzmann-Gibbs (BG) and nonextensive statistical mechanics can be seen through three different stages. First, the proposal of an entropic functional ($S_{BG} =-k\sum_i p_i \ln p_i$ for the BG formalism) with the…

Statistical Mechanics · Physics 2016-08-31 Constantino Tsallis , Andre M. C. Souza

When network and graph theory are used in the study of complex systems, a typically finite set of nodes of the network under consideration is frequently either explicitly or implicitly considered representative of a much larger finite or…

Data Analysis, Statistics and Probability · Physics 2015-03-18 Jobst Heitzig , Jonathan F. Donges , Yong Zou , Norbert Marwan , Jürgen Kurths

In this paper we analyze the spin-wave excitations (magnons) of an inhomogeneous spin system within the Boltzmann-Gibbs framework and then connect the results with the nonextensive approach (in the sense of Tsallis statistics). Considering…

Statistical Mechanics · Physics 2009-11-13 D. O. Soares-Pinto , M. S. Reis , R. S. Sarthour , I. S. Oliveira

We discuss the possibility of implementing axiomatic nonextensive statistics, where it is conjectured that the phase-space volume determines the (non)extensive entropy, on the particle production at NICA energies. Both Boltzmann-Gibbs and…

Nuclear Theory · Physics 2016-08-23 Abdel Nasser Tawfik

The area of networks is very interdisciplinary and exhibits many applications in several fields of science. Nevertheless, there are few studies focusing on geographically located $d$-dimensional networks. In this paper, we study scaling…

Statistical Mechanics · Physics 2019-01-09 Samuraí Brito , Thiago C. Nunes , Luciano R. da Silva , Constantino Tsallis

It has been argued in [EPL {\bf 90} (2010) 50004], entitled {\it Essential discreteness in generalized thermostatistics with non-logarithmic entropy}, that "continuous Hamiltonian systems with long-range interactions and the so-called…

Statistical Mechanics · Physics 2017-08-23 A. Plastino , M. C. Rocca

Gravity is so different from other fundamental forces that it is now essentially treated as a non-fundamental force of entropic origin. A number of good studies have been carried out in this direction. Quantum gravity has also significantly…

General Relativity and Quantum Cosmology · Physics 2020-12-11 M. Hameeda , Q. Gani , B. Pourhassan , M. C. Rocca

The study of complex systems is limited by the fact that only few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the systems behavior. In addition, empirical data typically…

Data Analysis, Statistics and Probability · Physics 2013-11-04 Matteo Marsili , Iacopo Mastromatteo , Yasser Roudi

To describe high energy collisions one widely uses thermodynamical methods and concepts which follow the classical Boltzmann-Gibbs (BG) approach. In many cases, however, either some deviations from the expected behaviour are observed…

High Energy Physics - Phenomenology · Physics 2015-06-25 G. Wilk , Z. Wlodarczyk

A well-known result across information theory, machine learning, and statistical physics shows that the maximum entropy distribution under a mean constraint has an exponential form called the Gibbs-Boltzmann distribution. This is used for…

Machine Learning · Computer Science 2020-06-26 Amir R. Asadi , Emmanuel Abbe

Recently a number of approaches has been developed to connect the microscopic dynamics of particle systems to the macroscopic properties of systems in nonequilibrium stationary states, via the theory of dynamical systems. This way a direct…

Statistical Mechanics · Physics 2009-10-31 L. Rondoni , E. G. D. Cohen

The exponential family of random graphs represents an important and challenging class of network models. Despite their flexibility, conventionally used exponential random graphs have one shortcoming. They cannot directly model weighted…

Probability · Mathematics 2016-07-15 Mei Yin