Spatial resonance and Turing–Hopf bifurcations in the Gierer–Meinhardt model. (October 2016)

• Record Type: Journal Article
• Authors: Yang, Rui; Song, Yongli
• Is Part Of: Nonlinear analysis. Volume 31(2016)
• Page Start: 356
• Page End: 387
• Publication Date: 2016-10
• Subjects: Gierer–Meinhardt model -- Spatial resonance bifurcation -- Turing–Hopf bifurcation -- Normal form -- Dynamical classification; Nonlinear functional analysis -- Periodicals; Analyse fonctionnelle non linéaire -- Périodiques; Nonlinear functional analysis; Periodicals; 515.7248
• DOI: 10.1016/j.nonrwa.2016.02.006
• Languages: English
• ISSNs: 1468-1218

Abstract

Abstract: Gierer–Meinhardt system as a molecularly plausible model has been proposed to formalize the observation for pattern formation. In this paper, the Gierer–Meinhardt model without the saturating term is considered. By the linear stability analysis, we not only give out the conditions ensuring the stability and Turing instability of the positive equilibrium but also find the parameter values where possible Turing–Hopf and spatial resonance bifurcation can occur. Then we develop the general algorithm for the calculations of normal form associated with codimension-2 spatial resonance bifurcation to better understand the dynamics neighboring of the bifurcating point. The spatial resonance bifurcation reveals the interaction of two steady state solutions with different modes. Numerical simulations are employed to illustrate the theoretical results for both the Turing–Hopf bifurcation and spatial resonance bifurcation. Some expected solutions including stable spatially inhomogeneous periodic solutions and coexisting stable spatially steady state solutions evolve from Turing–Hopf bifurcation and spatial resonance bifurcation respectively. Highlights: Obtain the algorithm of normal form for the spatial resonance bifurcation. Study the dynamics of the GM model near the codimension-2 bifurcation point. Obtain the existence of multiple spatially inhomogeneous equilibria for GM model. Obtain the stable spatially inhomogeneous periodic solutions for GM model.