8 research outputs found
Turing Instability and Pattern Formation in an Activator-Inhibitor System with Nonlinear Diffusion
In this work we study the effect of density dependent nonlinear diffusion on
pattern formation in the Lengyel--Epstein system. Via the linear stability
analysis we determine both the Turing and the Hopf instability boundaries and
we show how nonlinear diffusion intensifies the tendency to pattern formation;
%favors the mechanism of pattern formation with respect to the classical linear
diffusion case; in particular, unlike the case of classical linear diffusion,
the Turing instability can occur even when diffusion of the inhibitor is
significantly slower than activator's one. In the Turing pattern region we
perform the WNL multiple scales analysis to derive the equations for the
amplitude of the stationary pattern, both in the supercritical and in the
subcritical case. Moreover, we compute the complex Ginzburg-Landau equation in
the vicinity of the Hopf bifurcation point as it gives a slow spatio-temporal
modulation of the phase and amplitude of the homogeneous oscillatory solution.Comment: Accepted for publication in Acta Applicandae Mathematica
Turing pattern formation in the Brusselator system with nonlinear diffusion
In this work we investigate the effect of density dependent nonlinear
diffusion on pattern formation in the Brusselator system. Through linear
stability analysis of the basic solution we determine the Turing and the
oscillatory instability boundaries. A comparison with the classical linear
diffusion shows how nonlinear diffusion favors the occurrence of Turing pattern
formation. We study the process of pattern formation both in 1D and 2D spatial
domains. Through a weakly nonlinear multiple scales analysis we derive the
equations for the amplitude of the stationary patterns. The analysis of the
amplitude equations shows the occurrence of a number of different phenomena,
including stable supercritical and subcritical Turing patterns with multiple
branches of stable solutions leading to hysteresis. Moreover we consider
traveling patterning waves: when the domain size is large, the pattern forms
sequentially and traveling wavefronts are the precursors to patterning. We
derive the Ginzburg-Landau equation and describe the traveling front enveloping
a pattern which invades the domain. We show the emergence of radially symmetric
target patterns, and through a matching procedure we construct the outer
amplitude equation and the inner core solution.Comment: Physical Review E, 201
Pattern selection in the Schnakenberg equations: From normal to anomalous diffusion
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, the 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.Comment: 18 pages, 13 figure
Towards an Efficient Finite Element Method for the Integral Fractional Laplacian on Polygonal Domains
We explore the connection between fractional order partial differential
equations in two or more spatial dimensions with boundary integral operators to
develop techniques that enable one to efficiently tackle the integral
fractional Laplacian. In particular, we develop techniques for the treatment of
the dense stiffness matrix including the computation of the entries, the
efficient assembly and storage of a sparse approximation and the efficient
solution of the resulting equations. The main idea consists of generalising
proven techniques for the treatment of boundary integral equations to general
fractional orders. Importantly, the approximation does not make any strong
assumptions on the shape of the underlying domain and does not rely on any
special structure of the matrix that could be exploited by fast transforms. We
demonstrate the flexibility and performance of this approach in a couple of
two-dimensional numerical examples
Pattern selection models: From normal to anomalous diffusion
“Pattern formation and selection is an important topic in many physical, chemical, and biological fields. In 1952, Alan Turing showed that a system of chemical substances could produce spatially stable patterns by the interplay of diffusion and reactions. Since then, pattern formations have been widely studied via the reaction-diffusion models. So far, patterns in the single-component system with normal diffusion have been well understood. Motivated by the experimental observations, more recent attention has been focused on the reaction-diffusion systems with anomalous diffusion as well as coupled multi-component systems. The objectives of this dissertation are to study the effects of superdiffusion on pattern formations and to compare them with the effects of normal diffusion in one-, and multi-component reaction-diffusion systems. Our studies show that the model parameters, including diffusion coefficients, ratio of diffusion powers, and coupling strength between components play an important role on the pattern formation. Both theoretical analysis and numerical simulations are carried out to understand the pattern formation in different parameter regimes. Starting with the linear stability analysis, the theoretical studies predict the space of Turing instability. To further study pattern selection in this space, weakly nonlinear analysis is carried out to obtain the regimes for different patterns. On the other hand, numerical simulations are carried out to fully investigate the interplay of diffusion and nonlinear reactions on pattern formations. To this end, the reaction-diffusion systems are solved by the Fourier pseudo-spectral method. Numerical results show that superdiffusion may substantially change the patterns in a reaction-diffusion system. Different superdiffusive exponents of the activator and inhibitor could cause both qualitative and quantitative changes in emergent spatial patterns. Comparing to single-component systems, the patterns observed in multi-component systems are more complex”--Abstract, page iv