From Langevin dynamics to kinetic Monte Carlo: the quasi-stationary distribution approach
Ecole des Ponts ParisTech, France
We will present a mathematical framework to draw a rigorous connection between microscopic and mesoscopic models to describe the evolutions of materials at the atomistic scale: molecular dynamics, namely Langevin or overdamped Langevin dynamics, and kinetic Monte Carlo (a.k.a. Markov State Models), namely jump Markov processes with values in a discrete state space. This analysis is useful to analyze and justify numerical methods which use the jump Markov model underlying the molecular dynamics as a support to efficiently sample the state-to-state dynamics (accelerated dynamics techniques à la D. Perez and A.F. Voter). It also provides a mathematical framework to justify the use of transition state theory and the Eyring-Kramers formula to build kinetic Monte Carlo or Markov state models.
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