Global Attractors and Random Attractors of Reaction-Diffusion Systems

• Main Author: Tu, Junyi
• Format: Others
• Published: Scholar Commons 2016
• Subjects: Global Attractor; Random Attractor; Boissonade Equations; Stochastic Brusselator; Applied Mathematics; Systems Biology
• Online Access: http://scholarcommons.usf.edu/etd/6418; http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=7614&context=etd

The dissertation studies about the existence of three different types of attractors of three multi-component reaction-diffusion systems. These reaction-diffusion systems play important role in both chemical kinetics and biological pattern formation in the fast-growing area of mathematical biology. In Chapter 2, we prove the existence of a global attractor and an exponential attractor for the solution semiflow of a reaction-diffusion system called Boissonade equations in the L2 phase space. We show that the global attractor is an (H, E) global attractor with the L∞ and H2 regularity and that the Hausdorff dimension and the fractal dimension of the global attractor are finite. The existence of exponential attractor is also shown. The upper-semicontinuity of the global attractors with respect to the reverse reaction rate coefficient is proved. In Chapter 3, the existence of a pullback attractor for non-autonomous reversible Selkov equations in the product L2 phase space is proved. The method of grouping and rescaling estimation is used to prove that the L4-norm and L6-norm of solution trajectories are asymptotic bounded. The new feature of pinpointing a middle time in the process turns out to be crucial to deal with the challenge in proving pullback asymptotic compactness of this typical non-autonomous reaction-diffusion system. In Chapter 4, asymptotical dynamics of stochastic Brusselator equations with multiplicative noise is investigated. The existence of a random attractor is proved via the exponential transformation of Ornstein-Uhlenbeck process and some challenging estimates. The proof of pullback asymptotic compactness here is more rigorous through the bootstrap pullback estimation than a non-dynamical substitution of Brownian motion by its backward translation. It is also shown that the random attractor has the L2 to H1 attracting regularity by the flattening method.