Abstract
In this paper, we explore the role of network topology on maintaining the extensive property of entropy. We study analytically and numerically how the topology contributes to maintaining extensivity of entropy in multiplex networks, i.e. networks of subnetworks (layers), by means of the sum of the positive Lyapunov exponents, HKS, a quantity related to entropy. We show that extensivity relies not only on the interplay between the coupling strengths of the dynamics associated to the intra (short-range) and inter (long-range) interactions, but also on the sum of the intra-degrees of the nodes of the layers. For the analytically treated networks of size N, among several other results, we show that if the sum of the intra-degrees (and the sum of inter-degrees) scales as Nθ+1, θ > 0, extensivity can be maintained if the intra-coupling (and the inter-coupling) strength scales as N-θ, when evolution is driven by the maximisation of HKS. We then verify our analytical results by performing numerical simulations in multiplex networks formed by electrically and chemically coupled neurons.
| Original language | English |
|---|---|
| Article number | e0175389 |
| Journal | PloS ONE |
| Volume | 12 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 12 Apr 2017 |
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Maintaining extensivity in evolutionary multiplex networks. / Antonopoulos, Chris G; Baptista, Murilo S.
In: PloS ONE, Vol. 12, No. 4, e0175389, 12.04.2017.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Maintaining extensivity in evolutionary multiplex networks
AU - Antonopoulos, Chris G
AU - Baptista, Murilo S.
N1 - Funding: C. G. A. and M. S. B. acknowledge financial support provided by the Engineering and Physical Sciences Research Council (EPSRC) (https://www.epsrc.ac.uk/) Ref: EP/I032606/1 grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
PY - 2017/4/12
Y1 - 2017/4/12
N2 - In this paper, we explore the role of network topology on maintaining the extensive property of entropy. We study analytically and numerically how the topology contributes to maintaining extensivity of entropy in multiplex networks, i.e. networks of subnetworks (layers), by means of the sum of the positive Lyapunov exponents, HKS, a quantity related to entropy. We show that extensivity relies not only on the interplay between the coupling strengths of the dynamics associated to the intra (short-range) and inter (long-range) interactions, but also on the sum of the intra-degrees of the nodes of the layers. For the analytically treated networks of size N, among several other results, we show that if the sum of the intra-degrees (and the sum of inter-degrees) scales as Nθ+1, θ > 0, extensivity can be maintained if the intra-coupling (and the inter-coupling) strength scales as N-θ, when evolution is driven by the maximisation of HKS. We then verify our analytical results by performing numerical simulations in multiplex networks formed by electrically and chemically coupled neurons.
AB - In this paper, we explore the role of network topology on maintaining the extensive property of entropy. We study analytically and numerically how the topology contributes to maintaining extensivity of entropy in multiplex networks, i.e. networks of subnetworks (layers), by means of the sum of the positive Lyapunov exponents, HKS, a quantity related to entropy. We show that extensivity relies not only on the interplay between the coupling strengths of the dynamics associated to the intra (short-range) and inter (long-range) interactions, but also on the sum of the intra-degrees of the nodes of the layers. For the analytically treated networks of size N, among several other results, we show that if the sum of the intra-degrees (and the sum of inter-degrees) scales as Nθ+1, θ > 0, extensivity can be maintained if the intra-coupling (and the inter-coupling) strength scales as N-θ, when evolution is driven by the maximisation of HKS. We then verify our analytical results by performing numerical simulations in multiplex networks formed by electrically and chemically coupled neurons.
U2 - 10.1371/journal.pone.0175389
DO - 10.1371/journal.pone.0175389
M3 - Article
C2 - 28403162
VL - 12
JO - PloS ONE
JF - PloS ONE
SN - 1932-6203
IS - 4
M1 - e0175389
ER -