The 2015 AMMCS-CAIMS Congress
Interdisciplinary AMMCS Conference Series
Waterloo, Ontario, Canada | June 7-12, 2015AMMCS-CAIMS 2015 Plenary Talk
Multiscale Modeling in a Stochastic Setting
Eric Vanden-Eijnden (Courant Institute, New York University)
Applications from molecular dynamics, material science, biology, or
atmosphere/ocean sciences present new challenges for applied and numerical
mathematics. These applications typically involve systems whose dynamics span a
very wide range of spatio-temporal scales, and are subject to random
perturbations of thermal or other origin. This second aspect especially
complicates the modeling and computation of these systems and requires one to
revisit standard tools from numerical analysis from a probabilistic
perspective. In this talk I will discuss recent advances that have been made in
this context. For example, I will show how tools from Freidlin-Wentzell theory
of large deviations and potential theoretic approaches to metastability can be
used to develop numerical algorithms to accelerate the computations of reactive
events arising in metastable systems. I will also explain how averaging
theorems for singularly perturbed Markov processes can help develop schemes
bridging micro- to macro-scales of description or compute free energies, etc.
As illustrations, I will use a selection of examples from molecular dynamics,
material sciences, and fluid dynamics and show how the confrontation with
actual problems not only profits from the theory but also enriches it.
My main focus is the development of mathematical tools and numerical methods
for the analysis of dynamical systems which are both stochastic and multiscale.
The particular areas of applications I am interested in include molecular
dynamics, chemical and biological networks, materials science, atmosphere-ocean
science, and fluids dynamics. My main objectives are to understand the pathways
and rate of occurrence of rare events in complex systems; to develop and
analyze multiscale algorithms for the simulation of random dynamical systems;
and, more generally, to quantify the effects of random perturbations on the
systems dynamics.