Turing pattern or system heterogeneity? A numerical continuation approach to assessing the role of Turing instabilities in heterogeneous reaction-diffusion systems
Jacob C. Vandenberg, Mark B. Flegg

TL;DR
This paper introduces a numerical continuation framework to analyze the role of Turing instabilities in heterogeneous reaction-diffusion systems, revealing complex behaviors and conditions under which patterns form or become indistinguishable from base states.
Contribution
The work develops a novel numerical continuation approach to map heterogeneous systems onto homogeneous ones, aiding in understanding Turing pattern formation amid heterogeneity.
Findings
Large heterogeneity can cause Turing and base states to coincide.
Localized morphogen production can support Turing patterns without classical domain boundaries.
Heterogeneity and local production alter critical domain lengths and pattern coupling.
Abstract
Turing patterns in reaction-diffusion (RD) systems have classically been studied only in RD systems which do not explicitly depend on independent variables such as space. In practise, many systems for which Turing patterning is important are not homogeneous with ideal boundary conditions. In heterogeneous systems with stable steady states, the steady states are also necessarily heterogeneous which is problematic for applying the classical analysis. Whilst there has been some work done to extend Turing analysis to some heterogeneous systems, for many systems it is still difficult to determine if a stable patterned state is driven purely by system heterogeneity or if a Turing instability is playing a role. In this work, we try to define a framework which uses numerical continuation to map heterogeneous RD systems onto a sensible nearby homogeneous system. This framework may be used for…
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Taxonomy
TopicsNonlinear Dynamics and Pattern Formation · Cellular Automata and Applications · Theoretical and Computational Physics
