Finite propagation enhances Turing patterns in reaction-diffusion networked systems

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Autori principali: Carletti, Timoteo, Muolo, Riccardo
Natura: Preprint
Pubblicazione: 2021
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author Carletti, Timoteo
Muolo, Riccardo
author_facet Carletti, Timoteo
Muolo, Riccardo
contents We hereby develop the theory of Turing instability for reaction-diffusion systems defined on complex networks assuming finite propagation. Extending to networked systems the framework introduced by Cattaneo in the 40's, we remove the unphysical assumption of infinite propagation velocity holding for reaction-diffusion systems, thus allowing to propose a novel view on the fine tuning issue and on existing experiments. We analytically prove that Turing instability, stationary or wave-like, emerges for a much broader set of conditions, e.g., once the activator diffuses faster than the inhibitor or even in the case of inhibitor-inhibitor systems, overcoming thus the classical Turing framework. Analytical results are compared to direct simulations made on the FitzHugh-Nagumo model, extended to the relativistic reaction-diffusion framework with a complex network as substrate for the dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2104_04319
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle Finite propagation enhances Turing patterns in reaction-diffusion networked systems
Carletti, Timoteo
Muolo, Riccardo
Pattern Formation and Solitons
Mathematical Physics
Dynamical Systems
Adaptation and Self-Organizing Systems
We hereby develop the theory of Turing instability for reaction-diffusion systems defined on complex networks assuming finite propagation. Extending to networked systems the framework introduced by Cattaneo in the 40's, we remove the unphysical assumption of infinite propagation velocity holding for reaction-diffusion systems, thus allowing to propose a novel view on the fine tuning issue and on existing experiments. We analytically prove that Turing instability, stationary or wave-like, emerges for a much broader set of conditions, e.g., once the activator diffuses faster than the inhibitor or even in the case of inhibitor-inhibitor systems, overcoming thus the classical Turing framework. Analytical results are compared to direct simulations made on the FitzHugh-Nagumo model, extended to the relativistic reaction-diffusion framework with a complex network as substrate for the dynamics.
title Finite propagation enhances Turing patterns in reaction-diffusion networked systems
topic Pattern Formation and Solitons
Mathematical Physics
Dynamical Systems
Adaptation and Self-Organizing Systems
url https://arxiv.org/abs/2104.04319