Renormalization Group (RG) theory provides the theoretical framework to define rigorous effective theories, i.e., systematic low-resolution approximations of arbitrary microscopic models. Markov state models are shown to be rigorous effective theories for Molecular Dynamics (MD). Based on this fact, we use real space RG to vary the resolution of the stochastic model and define an algorithm for clustering microstates into macrostates. The result is a lower dimensional stochastic model which, by construction, provides the optimal coarse-grained Markovian representation of the system's relaxation kinetics. To illustrate and validate our theory, we analyze a number of test systems of increasing complexity, ranging from synthetic toy models to two realistic applications, built form all-atom MD simulations. The computational cost of computing the low-dimensional model remains affordable on a desktop computer even for thousands of microstates.

Orioli, S., Faccioli, P. (2016). Dimensional reduction of Markov state models from renormalization group theory. THE JOURNAL OF CHEMICAL PHYSICS, 145(12) [10.1063/1.4963196].

Dimensional reduction of Markov state models from renormalization group theory

Faccioli, Pietro
2016

Abstract

Renormalization Group (RG) theory provides the theoretical framework to define rigorous effective theories, i.e., systematic low-resolution approximations of arbitrary microscopic models. Markov state models are shown to be rigorous effective theories for Molecular Dynamics (MD). Based on this fact, we use real space RG to vary the resolution of the stochastic model and define an algorithm for clustering microstates into macrostates. The result is a lower dimensional stochastic model which, by construction, provides the optimal coarse-grained Markovian representation of the system's relaxation kinetics. To illustrate and validate our theory, we analyze a number of test systems of increasing complexity, ranging from synthetic toy models to two realistic applications, built form all-atom MD simulations. The computational cost of computing the low-dimensional model remains affordable on a desktop computer even for thousands of microstates.
Articolo in rivista - Articolo scientifico
Physics and Astronomy (all); Physical and Theoretical Chemistry
English
2016
145
12
124120
none
Orioli, S., Faccioli, P. (2016). Dimensional reduction of Markov state models from renormalization group theory. THE JOURNAL OF CHEMICAL PHYSICS, 145(12) [10.1063/1.4963196].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/405577
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