Position-dependent memory kernel in generalized Langevin equations: Theory and numerical estimation - Sorbonne Université
Article Dans Une Revue The Journal of Chemical Physics Année : 2022

Position-dependent memory kernel in generalized Langevin equations: Theory and numerical estimation

Résumé

Generalized Langevin equations with non-linear forces and position-dependent linear friction memory kernels, such as commonly used to describe the effective dynamics of coarse-grained variables in molecular dynamics, are rigorously derived within the Mori–Zwanzig formalism. A fluctuation–dissipation theorem relating the properties of the noise to the memory kernel is shown. The derivation also yields Volterra-type equations for the kernel, which can be used for a numerical parametrization of the model from all-atom simulations.
Fichier principal
Vignette du fichier
revision_jcp.pdf (2.73 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03714956 , version 1 (06-07-2022)

Identifiants

Citer

Hadrien Vroylandt, Pierre Monmarché. Position-dependent memory kernel in generalized Langevin equations: Theory and numerical estimation. The Journal of Chemical Physics, 2022, 156 (24), pp.244105. ⟨10.1063/5.0094566⟩. ⟨hal-03714956⟩
65 Consultations
55 Téléchargements

Altmetric

Partager

More