English

Finite propagation enhances Turing patterns in reaction-diffusion networked systems

Pattern Formation and Solitons 2025-10-22 v3 Mathematical Physics Dynamical Systems math.MP Adaptation and Self-Organizing Systems

Abstract

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.

Keywords

Cite

@article{arxiv.2104.04319,
  title  = {Finite propagation enhances Turing patterns in reaction-diffusion networked systems},
  author = {Timoteo Carletti and Riccardo Muolo},
  journal= {arXiv preprint arXiv:2104.04319},
  year   = {2025}
}
R2 v1 2026-06-24T00:59:55.697Z