2024/05/25 by Matteo Colangeli, Manh Hong Duong, Colangeli, Matteo +3 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #FOS: Mathematics #FOS: Physical sciences #Gaussian Processes and Bayesian Inference #Mathematical Physics (math-ph) #Model Reduction and Neural Networks #Probability (math.PR) #Protein Structure and Dynamics #Statistical Mechanics (cond-mat.stat-mech)
paper · pdf · doi:10.48550/arxiv.2405.16157
openalex publication_date 2024/05/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider a classical model of non-equilibrium statistical mechanics accounting for non-Markovian effects, which is referred to as the Generalized Langevin Equation in the literature. We derive reduced Markovian descriptions obtained through the neglection of inertial terms and/or heat bath variables. The adopted reduction scheme relies on the framework of the Invariant Manifold method, which allows to retain the slow degrees of freedom from a multiscale dynamical system. Our approach is also rooted on the Fluctuation-Dissipation Theorem, which helps preserve the proper dissipative structure of the reduced dynamics. We highlight the appropriate time scalings introduced within our procedure, and also prove the commutativity of selected reduction paths.