From Langevin dynamics to kinetic Monte Carlo: mathematical foundations of accelerated dynamics algorithms
Tony Lelièvre (Ecole des Ponts ParisTech)
Occasion: Mathematical and Computational Materials Science
Date: February 17, 2021
Abstract: We will discuss models used in classical molecular dynamics, and some mathematical questions raised by their simulations. In particular, we will present recent results on the connection between a metastable Markov process with values in a continuous state space (satisfying e.g. the Langevin or overdamped Langevin equation) and a jump Markov process with values in a discrete state space. This is useful to analyze and justify numerical methods which use the jump Markov process underlying a metastable dynamics as a support to efficiently sample the state-to-state dynamics (accelerated dynamics techniques à la 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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