A Numerical Procedure to Evaluate Memory Effects in Non‐Equilibrium Coarse‐Grained Models
Hugues Meyer, Steffen Wolf, Gerhard Stock, Tanja Schilling
Abstract
Abstract When developing coarse‐grained models of complex processes out of equilibrium, one encounters the non‐stationary generalized Langevin equation. The most important feature of this equation is the presence of a non‐stationary memory kernel. Here, a method is presented to infer this memory kernel from MD simulation data in non‐equilibrium processes. The method provides an improvement of a previously published numerical scheme, the applicability of which is limited by a truncation problem. As an illustration, the method is applied to ion dissociation of NaCl in water, for which non‐trivial dampened oscillations are observed in the memory kernel.
Topics & Concepts
Kernel (algebra)Computer scienceApplied mathematicsTruncation (statistics)Statistical physicsMathematicsPhysicsMachine learningCombinatoricsSpectroscopy and Quantum Chemical StudiesProtein Structure and DynamicsNanopore and Nanochannel Transport Studies