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SUMMARY:Metastability and Monte Carlo Methods for Multiscale Problems - Ko
 nstantinos Spiliopoulos ()
DTSTART:20160621T084500Z
DTEND:20160621T093000Z
UID:TALK66530@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Rare events\, metastability and Monte Carlo methods for stocha
 stic dynamical  systems have been of central scientific interest for many 
 years now. In this  article we focus on rough energy landscapes\, that are
  modeled as multiscale  stochastic dynamical systems perturbed by small no
 ise. Large deviations deals  with the estimation of rare events. Depending
  on the type of interaction of the  fast scales with the strength of the n
 oise we get different behavior\, both for  the large deviations and for th
 e corresponding Monte Carlo methods. We describe  how to design asymptotic
 ally provably efficient importance sampling schemes for  the estimation of
  associated rare event probabilities\, such as exit  probabilities\,hittin
 g probabilities\, hitting times\, and expectations of  functionals of inte
 rest. Standard Monte Carlo methods perform poorly in these  kind of proble
 ms in the small noise limit. In the presence of multiple scales  one faces
  additional difficulties and straightforward adaptation of importance  sam
 pling schemes for standard small noise diffusions will not produce efficie
 nt  schemes. Theoretical results are supplemented by numerical simulation 
  studies.
LOCATION:Seminar Room 1\, Newton Institute
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