Numerical Integration of Chaotic Dynamics - Uncertainty Propagation & Vectorized Integration

Explore the concept of chaos and its sensitive dependence on initial conditions in this 20-minute video lecture. Learn about the importance of integrating a bundle of trajectories to propagate uncertainty in chaotic systems. Discover techniques for vectorizing numerical integration in Python and MATLAB to significantly improve algorithm efficiency. Follow along as the instructor demonstrates slow and fast MATLAB code examples, as well as a Python implementation. Gain insights into uncertainty propagation with trajectory bundles, and understand how to optimize your code for better performance when dealing with chaotic dynamics.