Spectral Map for Slow Collective Variables, Markovian Dynamics, and Transition State Ensembles.

ABSTRACT: Understanding the behavior of complex molecular systems is a fundamental problem in physical chemistry. To describe the long-time dynamics of such systems, which is responsible for their most informative characteristics, we can identify a few slow collective variables (CVs) while treating the remaining fast variables as thermal noise. This enables us to simplify the dynamics and treat it as diffusion in a free-energy landscape spanned by slow CVs, effectively rendering the dynamics Markovian. Our recent statistical learning technique, spectral map [Rydzewski, J. J. Phys. Chem. Lett. 2023, 14(22), 5216-5220], explores this strategy to learn slow CVs by maximizing a spectral gap of a transition matrix. In this work, we introduce several advancements into our framework, u

SUBMITTER: Rydzewski J 

PROVIDER: S-EPMC11428138 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature