Tsallis mapping in growing complex networks with fitness

TL;DR

This paper introduces Tsallis mapping into the Bianconi-Barabási fitness model of growing networks, revealing how a nonextensive parameter influences network evolution and phase transitions within a nonextensive statistical mechanics framework.

Contribution

It presents a novel application of Tsallis nonextensive statistics to the fitness model, highlighting the impact of the nonextensivity parameter on network phase behavior.

Findings

The nonextensivity parameter q affects network phase transitions.

Different phases emerge depending on q values.

Critical transition temperature is identified.

Abstract

We introduce Tsallis mapping in Bianconi-Barab\'asi (B-B) fitness model of growing networks. This mapping addresses the dynamical behavior of the fitness model within the framework of nonextensive statistics mechanics, which is characterized by a dimensionless nonextensivity parameter $q$. It is found that this new phenomenological parameter plays an important role in the evolution of networks: the underlying evolving networks may undergo a different phases depending on the $q$ exponents, comparing to the original B-B fitness model, and the corresponding critical transition "temperature" is identified.