2024/09/13 by Evelyn Sander, Sander, E., James D. Meiss +1 · 1 citation
Computer Science · #34C37 #37C29 #37J45 #70H09 #AI-based Problem Solving and Planning #Chaotic Dynamics (nlin.CD) #Constraint Satisfaction and Optimization #Dynamical Systems (math.DS) #FOS: Mathematics #FOS: Physical sciences #Formal Methods in Verification
paper · pdf · doi:10.48550/arxiv.2409.08496
openalex publication_date 2024/09/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Lyapunov exponents of a dynamical system measure the average rate of exponential stretching along an orbit. Positive exponents are often taken as a defining characteristic of chaotic dynamics. However, the standard orthogonalization-based method for computing Lyapunov exponents converges slowly -- if at all. Many alternatively techniques have been developed to distinguish between regular and chaotic orbits, though most do not compute the exponents. We compute the Lyapunov spectrum in three ways: the standard method, the weighted Birkhoff average (WBA), and the ``mean exponential growth rate for nearby orbits'' (MEGNO). The latter two improve convergence for nonchaotic orbits, but the WBA is fastest. However, for chaotic orbits the three methods convergence at similar, slow rates. Though the original MEGNO method does not compute Lyapunov exponents, we show how to reformulate it as a weighted average that does.