Computing the Minimal Rebinding Effect for NonReversible Processes
Susanne Röhl, Marcus Weber, Konstantin Fackeldey · Multiscale Modeling and Simulation · 2021
The aim of this paper is to investigate the rebinding effect, a phenomenon describing a “short-time memory” which can occur when projecting a Markov process onto a smaller state space. For guaranteeing a correct mapping by the Markov state model, we assume a fuzzy clustering in terms of membership functions, assigning degrees of membership to each state. The macro states are represented by the membership functions and may be overlapping. The magnitude of this overlap is a measure for the strength of the rebinding effect, caused by the projection and stabilizing the system. A minimal bound for the rebinding effect included in a given system is computed as the solution of an optimization problem. Based on membership functions chosen as a linear combination of Schur vectors we are thus able to compute the minimal rebinding effect for nonreversible processes.