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Short-ranged memory model with preferential growth

Ana L. Schaigorodsky^*, Juan I. Perotti^†, Nahuel Almeira^‡, and Orlando V. Billoni^§

Instituto de Física Enrique Gaviola (IFEG-CONICET), Ciudad Universitaria, 5000 Córdoba, Argentina and Facultad de Matemática, Astronomía, Física y Computación, Universidad Nacional de Córdoba, 5000 Córdoba, Argentina

^*schaigorodsky@famaf.unc.edu.ar
^†juanpool@gmail.com
^‡nalmeira@famaf.unc.edu.ar
^§billoni@famaf.unc.edu.ar

Phys. Rev. E 97, 022132 – Published 20 February, 2018

DOI: https://doi.org/10.1103/PhysRevE.97.022132

Abstract

In this work we introduce a variant of the Yule-Simon model for preferential growth by incorporating a finite kernel to model the effects of bounded memory. We characterize the properties of the model combining analytical arguments with extensive numerical simulations. In particular, we analyze the lifetime and popularity distributions by mapping the model dynamics to corresponding Markov chains and branching processes, respectively. These distributions follow power laws with well-defined exponents that are within the range of the empirical data reported in ecologies. Interestingly, by varying the innovation rate, this simple out-of-equilibrium model exhibits many of the characteristics of a continuous phase transition and, around the critical point, it generates time series with power-law popularity, lifetime and interevent time distributions, and nontrivial temporal correlations, such as a bursty dynamics in analogy with the activity of solar flares. Our results suggest that an appropriate balance between innovation and oblivion rates could provide an explanatory framework for many of the properties commonly observed in many complex systems.

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