Computing the Invariant Measure and the Lyapunov Exponent for One-Dimensional Maps using a Measure-Preserving Polynomial Basis

Details Computing the Invariant Measure and the Lyapunov Exponent for One-Dimensional Maps using a Measure-Preserving Polynomial Basis Computing the Invariant Measure and the Lyapunov Exponent for One-Dimensional Maps using a Measure-Preserving Polynomial Basis

2011-11-25

arxiv.org/abs/1111.5947v1

Mathematics

Numerical Analysis

Scientific paper

We consider a generalisation of Ulam's method for approximating invariant densities of one-dimensional chaotic maps. Rather than use piecewise constant polynomials to approximate the density, we use polynomials of degree n which are defined by the requirement that they preserve the measure on n+1 neighbouring subintervals. Over the whole interval, this results in a discontinuous piecewise polynomial approximation to the density. We prove error results where this approach is used to approximate smooth densities. We also consider the computation of the Lyapunov exponent using the polynomial density and show that the order of convergence is one order better than for the density itself. Together with using cubic polynomials in the density approximation, this yields a very efficient method for computing highly accurate estimates of the Lyapunov exponent. We illustrate the theoretical findings with some examples.

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