3 papers
nlin.CD2026
Noise-Induced Predictability Redistribution Across Forecast Horizons of Extreme Events in Chaotic Dynamics
Andrei Velichko, Viet-Thanh Pham
Extreme events (EEs) in chaotic dynamics are rare broad excursions whose forecastability can be altered by dynamical noise. We investigate how noise changes EE occurrence and predi…
nlin.CD2026
When More Data Become Less Informative: Finite-Precision Periodicization and Collapse of Forecast-Error Lyapunov Estimates
Andrei Velichko, Viet-Thanh Pham
Largest Lyapunov exponents (LLEs) quantify exponential sensitivity, but data-driven estimates are often obtained from finite-precision trajectories. We show that increasing the len…
nlin.CD2026
Equation-Free Period-Aware Forecast-Error Contraction for Estimating Negative Largest Lyapunov Exponents from Short Trajectory Ensembles
Andrei Velichko, N'Gbo N'Gbo, Viet-Thanh Pham
Estimating positive largest Lyapunov exponents from data is comparatively natural because neighboring trajectories separate, whereas stable dynamics require resolving contraction b…