4.4 Article

Bifurcation Analysis of Reaction Diffusion Systems on Arbitrary Surfaces

期刊

BULLETIN OF MATHEMATICAL BIOLOGY
卷 79, 期 4, 页码 788-827

出版社

SPRINGER
DOI: 10.1007/s11538-017-0255-8

关键词

Reaction diffusion; Pattern formation; Bifurcation analysis; Linear stability analysis; Marginal stability analysis; Branch tracing; Nonlinear PDEs; Surface FEMs; Large-scale systems; Multigrid approach; Cross-diffusion

资金

  1. Swiss National Science Foundation (FNSNF) [31003A_140785, SINERGIA CRSII3_132430]
  2. SystemsX.ch initiative (project Epi-PhysX)
  3. FNSNF [SINERGIA CRSII3_132430]
  4. Swiss National Science Foundation (SNF) [31003A_140785] Funding Source: Swiss National Science Foundation (SNF)

向作者/读者索取更多资源

In this paper, we present computational techniques to investigate the effect of surface geometry on biological pattern formation. In particular, we study two-component, nonlinear reaction-diffusion (RD) systems on arbitrary surfaces. We build on standard techniques for linear and nonlinear analysis of RD systems and extend them to operate on large-scale meshes for arbitrary surfaces. In particular, we use spectral techniques for a linear stability analysis to characterise and directly compose patterns emerging from homogeneities. We develop an implementation using surface finite element methods and a numerical eigenanalysis of the Laplace-Beltrami operator on surface meshes. In addition, we describe a technique to explore solutions of the nonlinear RD equations using numerical continuation. Here, we present a multiresolution approach that allows us to trace solution branches of the nonlinear equations efficiently even for large-scale meshes. Finally, we demonstrate the working of our framework for two RD systems with applications in biological pattern formation: a Brusselator model that has been used to model pattern development on growing plant tips, and a chemotactic model for the formation of skin pigmentation patterns. While these models have been used previously on simple geometries, our framework allows us to study the impact of arbitrary geometries on emerging patterns.

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