Nonlinear Normal Mode

Nonlinear normal modes (NNMs) describe the oscillatory behavior of nonlinear systems, extending the concept of linear normal modes to more complex scenarios. Current research focuses on leveraging NNMs for model reduction in diverse fields, employing techniques like deep learning to efficiently capture complex dynamics and identify key features, such as in plasma physics and soft robotics. This work aims to improve model accuracy and efficiency for control and simulation, particularly in systems with high dimensionality or intricate multiphysics interactions, as demonstrated by applications ranging from robotic control to gravitational wave detection. The ability to accurately and efficiently model nonlinear systems using NNMs has significant implications for various scientific disciplines and engineering applications.