Preserving the Markov Property of Reduced Reversible Markov Chains
M. Weber, S. Kube – 2008
The computation of essential dynamics of molecular systems by conformation dynamics turned out to be very successful. This approach is based on Markov chain Monte Carlo simulations. Conformation dynamics aims at decomposing the state space of the system into metastable subsets. The set‐based reduction of a Markov chain, however, destroys the Markov property. We will present an alternative reduction method that is not based on sets but on membership vectors, which are computed by the Robust Perron Cluster Analysis (PCCA+). This approach preserves the Markov property.