Nepomuceno, Erivelton and Perc, Matjaž and Estrada, Ernesto (2019) Computational chaos in complex networks. Journal of Complex Networks, 8 (1). pp. 1-16. ISSN 2051-1329

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Abstract

Computational chaos reports the artificial generation or suppression of chaotic behaviour in digital computers. There is a significant interest of the scientific community in analysing and understanding computational chaos of discrete and continuous systems. Notwithstanding, computational chaos in complex networks has received much less attention. In this article, we report computational chaos in a network of coupled logistic maps. We consider two types of networks, namely the Erdös–Rényi random network and the Barabási–Albert scale-free network. We show that there is an emergence of computational chaos when two different natural interval extensions are used in the simulation. More surprisingly, we also show that this chaos can be suppressed by an average of natural interval extensions, which can thus be considered as a filter to reduce the uncertainty stemming from the inherent finite precision of computer simulations.

Item Type:	Article
Keywords:	computational chaos; chaos suppression; non-linear dynamics; complex networks; computer arithmetic; complex systems;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	16735
Identification Number:	https://doi.org/10.1093/comnet/cnz015
Depositing User:	Erivelton Nepomuceno
Date Deposited:	22 Nov 2022 14:02
Journal or Publication Title:	Journal of Complex Networks
Publisher:	Oxford University Press
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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