Courant Institute of Mathematical Sciences
Mathematics Colloquium
March 11, 2013
Speaker: Gabor Csanyi, University of Cambridge
Title: Practical use of information concepts in molecular simulation
Abstract:
In this talk I will show, through three examples, how simple concepts from applied
probability and machine learning have the potential to change the art of atomic and
molecular scale modelling. (i) Bayesian inference can be used to ensure the sound
treatment of information, thus maximising the utility of simulations, for example in
reconstructing free energy surfaces from molecular dynamics. (ii) In constructing
interatomic potential models, Gaussian processes are used to encode prior information
and lead to an unprecedented combination of accuracy and computational efficiency - as
demonstrated by the most accurate model of water to date that correctly captures the
behaviours of clusters, ice and liquid phases. (iii) a fresh look at the sampling problem in
the context of exploring potential energy landscapes yields a gain of many orders of
magnitude over 'replica exchange', and brings into clear focus one of the central problems
in molecular simulation: designing a process to minimise the decorrelation time or equivalently - to accelerate the convergence to any specified invariant distribution.