2018
DOI: 10.1103/physreve.97.040301
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Spontaneous repulsion in the A+B0 reaction on coupled networks

Abstract: We study the transient dynamics of an A+B→0 process on a pair of randomly coupled networks, where reactants are initially separated. We find that, for sufficiently small fractions q of cross couplings, the concentration of A (or B) particles decays linearly in a first stage and crosses over to a second linear decrease at a mixing time t_{x}. By numerical and analytical arguments, we show that for symmetric and homogeneous structures t_{x}∝(〈k〉/q)log(〈k〉/q) where 〈k〉 is the mean degree of both networks. Being t… Show more

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Cited by 5 publications
(4 citation statements)
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“…A community is a sub-graph with more internal than external connections, and as the number of internal links increases compared to the external ones, the network has a higher level of community structure or modularity [1,4]. Several theoretical studies have focused on studying models of networks with sub-graphs whose nodes are densely connected in order to understand the effect of the community structure on processes that develop on top of complex networks [5][6][7][8]. Disease spreading is one of the most studied dynamic processes since many diseases that emerge could become an epidemic, i.e., could affect a large number of people, or even could spread across the world and become a pandemic.…”
Section: Introductionmentioning
confidence: 99%
“…A community is a sub-graph with more internal than external connections, and as the number of internal links increases compared to the external ones, the network has a higher level of community structure or modularity [1,4]. Several theoretical studies have focused on studying models of networks with sub-graphs whose nodes are densely connected in order to understand the effect of the community structure on processes that develop on top of complex networks [5][6][7][8]. Disease spreading is one of the most studied dynamic processes since many diseases that emerge could become an epidemic, i.e., could affect a large number of people, or even could spread across the world and become a pandemic.…”
Section: Introductionmentioning
confidence: 99%
“…The individual who participates in both layers is represented by a bridge node in each layer, which is connected to each other through an external link. Several studies showed that simple multilayer networks boost the propagation of information [12], accelerate diffusion processes [13], delay reactions [14] and increase the virulence of diseases with respect to an isolated network [15].…”
Section: Introductionmentioning
confidence: 99%
“…order interactions networks (Lambiotte et al 2019;de Arruda et al 2020;Millán et al 2020). These structures were studied under different processes and dynamics such as percolation (Bunde and Havlin 1991;Stauffer and Aharony 2018), synchronization (Arenas et al 2006;Danziger et al 2019;De Domenico 2017), reaction-diffusion (Weber et al 2008;Cencetti et al 2018;Lazaridis et al 2018;Colizza et al 2007), and epidemics (Pastor-Satorras et al 2015;Boguá et al 2003;Wang et al 2017).…”
mentioning
confidence: 99%