Abstract

We consider reduction of dimension for nonlinear dynamical systems. We demonstrate that in some cases, one can reduce a nonlinear system of equations into a single equation for one of the state variables, and this can be useful for computing the solution when using a variety of analytical approaches. In the case where this reduction is possible, we employ differential elimination to obtain the reduced system. While analytical, the approach is algorithmic and is implemented in symbolic software such as MAPLE or SageMath. In other cases, the reduction cannot be performed strictly in terms of differential operators, and one obtains integro-differential operators, which may still be useful. In either case, one can use the reduced equation to both approximate solutions for the state variables and perform chaos diagnostics more efficiently than could be done for the original higher-dimensional system, as well as to construct Lyapunov functions which help in the large-time study of the state variables. A number of chaotic and hyperchaotic dynamical systems are used as examples in order to motivate the approach.

Highlights

  • Nonlinear dynamical systems are ubiquitous in mathematics, engineering, and the sciences, with many real-world phenomenon governed by such nonlinear processes

  • When applying the competitive modes analysis, we find that only one binary comparison is needed if one first reduces the dimension of the dynamical system so that there is a single equation for one state variable

  • We have observed that for more complicated nonlinear dynamical systems, there is no reduction to a single ordinary differential equation (ODE) in one state variable

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Summary

Introduction

Nonlinear dynamical systems are ubiquitous in mathematics, engineering, and the sciences, with many real-world phenomenon governed by such nonlinear processes. One method for reduction of dimension is differential elimination, in which one algorithmically reduces the nonlinear dynamical system into a single ordinary differential equation (ODE) for one of the state variables. When applying the competitive modes analysis (which is a type of diagnostic criteria for finding chaotic trajectories in nonlinear dynamical systems), we find that only one binary comparison is needed if one first reduces the dimension of the dynamical system so that there is a single equation for one state variable.

Algebraic approach to differential elimination
Algebra preliminaries
Computational method
Reduction of dimension: applications
Rössler system
Lorenz system
Qi–Chen–Du–Chen–Yuan system
Reductions of n-dimensional dynamical systems
Differentially irreducible nonlinear systems
Contraction maps and Lyapunov functions
Computational considerations for chaotic trajectories
Calculation of trajectories via undetermined coefficients
Competitive modes analysis: a check for chaos
Discussion
Conclusions
Full Text
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