The use of numerical simulation for prediction of characteristics of chaotic dynamical systems inherently involves unpredictable processes. In this work, we develop a model for the expected error in the simulation of ergodic, chaotic ODE systems, which allows for discretization and statistical effects due to unpredictability. Using this model, we then generate a framework for understanding the relationship between the sampling cost of a simulation and the expected error in the result, and explore the implications of the various parameters of simulations. Finally, we generalize the framework to consider the total cost – including unsampled spin-up timesteps – of simulations and consider the implications of parallel computational environments, to give a realistic model of the relationship between wall-clock time and the expected error in simulation of a chaotic ODE system.

生成讲解博客的中文版本

生成AI智能校验的中文版本