
We consider systems of differential equations with quadratic nonlinearities having applications for biochemistry and population dynamics, which may have a large dimension n. Due to the complexity of these systems, reduction algorithms play a crucial role in study of their large time behavior. Our approach aims to reduce a large system to a smaller one consisting of m differential equations, where . Under some restrictions (that allow us to separate slow and fast variables in the system) we obtain a new system of differential equations, involving slow variables only. This reduction is feasible from a computational point of view for large n that allows us to investigate sensitivity of dynamics with respect to random variations of parameters. We show that the quadratic systems are capable to generate all kinds of structurally stable dynamics including chaos.
Population dynamics (general), Biochemistry, molecular biology, chaos, reduction algorithms, Nonlinear ordinary differential equations and systems, quadratic nonlinearities
Population dynamics (general), Biochemistry, molecular biology, chaos, reduction algorithms, Nonlinear ordinary differential equations and systems, quadratic nonlinearities
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