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SUMMARY:Multilevel Monte Carlo simulation for scale-separated systems - Pa
 ul B. Rohrbach\, DAMTP
DTSTART:20200526T120000Z
DTEND:20200526T130000Z
UID:TALK142054@talks.cam.ac.uk
CONTACT:Etienne Fodor
DESCRIPTION:Designing efficient Monte Carlo simulations for multiscale phy
 sical systems is often a difficult problem. The underlying Markov chain ca
 n typically only modify the system locally on a small-scale level. This me
 ans that the long length-scale degrees of freedom of the system tend to de
 correlate very slowly. We propose a structured approach to circumvent slow
  simulations in this situation. Assume that the degrees of freedom corresp
 onding to the long length scales give rise to a coarse grained system whic
 h can be simulated efficiently. Instead of simulation the full system\, we
  first compute the coarse-grained approximation and subsequently correct t
 he coarse-graining error by a simulation of the remaining fine degrees of 
 freedom. This is inspired by the multilevel Monte Carlo approach that has 
 been developed in recent mathematical studies for applications in Bayesian
  inference and mathematical finance. We develop a convergence theory of ou
 r method and apply it to the Asakura-Oosawa (AO) model and size-asymmetric
 al binary hard-sphere systems. This allows us to investigate equilibrium p
 roperties of systems with a large size-ratio where a naive simulation woul
 d have been computationally infeasible.
LOCATION:Zoom: https://zoom.us/j/5916271322 Meeting ID: 591-627-1322
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