Molecular self-organization driven by concerted many-body interactions produces the
ordered structures that define both inanimate and living matter. Here we present an …

With the rapid increase of available data for complex systems, there is great interest in the
extraction of physically relevant information from massive datasets. Recently, a framework …

Transfer operators such as the Perron–Frobenius or Koopman operator play an important
role in the global analysis of complex dynamical systems. The eigenfunctions of these …

One of the main challenges in molecular dynamics is overcoming the 'timescale barrier': in
many realistic molecular systems, biologically important rare transitions occur on timescales …

We present a systematic approach to reduce the dimensionality of a complex molecular
system. Starting with a data set of molecular coordinates (obtained from experiment or …

In this work, we introduce a flow based machine learning approach called reaction
coordinate (RC) flow for the discovery of low-dimensional kinetic models of molecular …

Simulations are vital for understanding and predicting the evolution of complex molecular
systems. However, despite advances in algorithms and special purpose hardware …

Slow kinetic processes in molecular systems can be analyzed by computing the dominant
eigenpairs of the Koopman operator or its generator. In this context, the Variational …

The Journal of Chemical Physics article collection on Markov Models of Molecular Kinetics
(MMMK) features recent advances in develo** and using Markov State Models (MSMs) 1 …

One important problem in constructing the reduced dynamics of molecular systems is the
accurate modeling of the non-Markovian behavior arising from the dynamics of unresolved …