Metastable State

Metastable states, characterized by apparent stability over short timescales masking underlying instability, are a central focus in diverse scientific fields. Current research emphasizes developing computational methods, including deep learning architectures and reinforcement learning algorithms, to efficiently identify, characterize, and simulate transitions between these states in complex systems like molecules and neural networks. This work is crucial for advancing our understanding of dynamical systems across disciplines, enabling more accurate modeling of phenomena ranging from protein folding to neuromorphic computing and improving the design of physically intelligent robots.