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Unstable periodic orbits and discretization cycles.
P-M Binder1, Nicholas H Okamoto
1Department of Physics and Astronomy, University of Hawaii, Hilo, Hawaii 96720-4091, USA. pbinder@hawaii.edu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 20, 2003
Summary
Discretizing nonlinear maps typically creates limit cycles shadowing unstable periodic orbits (UPOs). However, some cycles require alternative explanations like near-UPOs or UPO crossovers.
Area of Science:
- Dynamical Systems
- Nonlinear Dynamics
- Computational Mathematics
Background:
- Limit cycles in discrete dynamical systems often arise from discretizing continuous nonlinear maps.
- These discrete cycles are generally understood to shadow unstable periodic orbits (UPOs) of the parent continuous system.
- However, discrepancies in this shadowing behavior necessitate further investigation into alternative mechanisms.
Purpose of the Study:
- To investigate the mechanisms behind limit cycles generated from discretizing nonlinear maps.
- To explore cases where discretization cycles do not directly shadow individual UPOs.
- To identify and characterize alternative explanations for observed limit cycle behavior.
Main Methods:
- Analysis of nonlinear maps and their discretization.
- Numerical simulation of discrete dynamical systems.
- Comparison of discrete limit cycles with unstable periodic orbits of continuous maps.
Main Results:
- Discretization of nonlinear maps generally produces limit cycles that shadow individual unstable periodic orbits (UPOs).
- In specific instances, discretization cycles cannot be solely explained by shadowing single UPOs.
- Alternative mechanisms, including the near-occurrence of UPOs or crossovers between multiple UPOs, are identified as explanations.
Conclusions:
- The shadowing of UPOs is a common but not exclusive phenomenon for limit cycles arising from discretization.
- The behavior of discrete limit cycles can be influenced by the proximity and interaction of multiple UPOs.
- Understanding these alternative mechanisms is crucial for accurately interpreting results from discretized nonlinear systems.