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SUMMARY:Metadynamics - Prof Michele Parinello\, ETH Zurich
DTSTART:20120309T160000Z
DTEND:20120309T170000Z
UID:TALK36800@talks.cam.ac.uk
CONTACT:Leona Hope-Coles
DESCRIPTION:Many systems like for instance biomolecules are characterized 
 by complex and rough potential energy surfaces and their behavior often re
 lies on a delicate balance between enthalpy and entropy.  Is such a cases 
 a simulation method has to find ways of addressing both the issue of accur
 ately sampling phase space and that of estimating free energies. Many tech
 niques have been proposed to this effect.  Here we discuss metadynamics wh
 ich is a powerful technique for enhancing sampling in molecular dynamics s
 imulations and reconstructing the free energy surface as a function of few
  selected degrees of freedom\, often referred to as collective variables (
 CVs). In metadynamics\, sampling is accelerated by a history- dependent bi
 as potential\, which is adaptively constructed in the space of the CVs. Si
 nce its first appearance\, significant improvements have been made to the 
 original algorithm\, leading to an efficient\, flexible and accurate metho
 d that has found many successful applications in several domains of scienc
 e. Here we discuss first the theory underlying metadynamics and its recent
  developments. In particular we focus on the crucial issue of choosing an 
 appropriate set of CVs and on the possible strategies to alleviate this di
 fficulty. \nIn a very recent development that we call reconnaissance metad
 ynamics\, we have applied methods borrowed from machine learning to recons
 truct the CVs. The principle and first applications of this very new appro
 ach will be also discussed.\n
LOCATION:Pippard Lecture Theatre\, Cavendish Laboratory\, Department of Ph
 ysics
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