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Pattern selection in the Schnakenberg equations: From normal to anomalous diffusion

Hatim K. Khudhair, Yanzhi Zhang, Nobuyuki Fukawa

2021Numerical Methods for Partial Differential Equations20 citationsDOI

Abstract

Abstract Pattern formation in the classical and fractional Schnakenberg equations is studied to understand the nonlocal effects of anomalous diffusion. Starting with linear stability analysis, we find that if the activator and inhibitor have the same diffusion power, the Turing instability space depends only on the ratio of diffusion coefficients . However, smaller diffusive powers might introduce larger unstable wave numbers with wider band, implying that the patterns may be more chaotic in the fractional cases. We then apply a weakly nonlinear analysis to predict the parameter regimes for spot, stripe, and mixed patterns in the Turing space. Our numerical simulations confirm the analytical results and demonstrate the differences of normal and anomalous diffusion on pattern formation. We find that in the presence of superdiffusion the patterns exhibit multiscale structures. The smaller the diffusion powers, the larger the unstable wave numbers, and the smaller the pattern scales.

Topics & Concepts

MathematicsAnomalous diffusionInstabilityTuringDiffusionStatistical physicsChaoticNonlinear systemWavenumberSpace (punctuation)Pattern formationMathematical analysisPhysicsQuantum mechanicsComputer scienceGeneticsInnovation diffusionKnowledge managementProgramming languageBiologyOperating systemArtificial intelligenceNonlinear Dynamics and Pattern FormationFractional Differential Equations SolutionsTheoretical and Computational Physics
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