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Nevanlinna–Pick interpolation of attractors

C Foias1,2, M S Jolly2 and W-S Li3,4

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Recommended by P Gaspard

A Nevanlinna–Pick algorithm is developed and applied to short numerical time series approximating trajectories of ordinary differential equations to determine whether the data are near the global attractor. The algorithm, while ultimately unstable to numerical error, is found to give reliable results for more data points than standard algorithms commonly used today. Connections between the growth of trajectories backward in time and the success in locating the global attractor are explored. The numerical sensitivity to both round-off errors and the integrator used to generate the time series is analysed. Applications are made to the Lorenz system and Kuramoto–Sivashinsky equation.


PACS

05.45.Tp Time series analysis

02.60.Lj Ordinary and partial differential equations; boundary value problems

02.60.Gf Algorithms for functional approximation

MSC

34L30 Nonlinear ordinary differential operators

65D15 Algorithms for functional approximation

37M10 Time series analysis

Subjects

Computational physics

Statistical physics and nonlinear systems

Dates

Issue 6 (November 2002)

Received 5 October 2001, in final form 16 June 2002

Published 23 September 2002



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