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BEGIN:VEVENT
DTSTAMP:20260414T083011Z
DTSTART;VALUE=DATE-TIME:20200511T130000
DTEND;VALUE=DATE-TIME:20200511T140000
SUMMARY:Variational coarse-graining and Mean First Passage Times in Marko
 v State Models
TZID:Europe/London
UID:20200511-8a17841a71405ebc0171bac8c0282f4a@warwick.ac.uk
CREATED:20200512T113017Z
DESCRIPTION:Alessia Annibale\, King's College London Markov State Models 
 (MSM) have gained large popularity in recent years as tools to interpret
  large time-series datasets from MD simulations and experiments\, and ha
 ve been successfully used to quantify and predict the dynamics of comple
 x biological processes\, such as protein folding\, molecular conformatio
 n and membrane crossing. However\, MSM also pose many interesting questi
 ons from a theoretical perspective\, for example: (i) how to identify op
 timal reaction coordinates (ii) how to choose the lag time at which the 
 MSM is constructed (iii) how to define optimal dimensionality reductions
 . In this talk we present a simple method to accurately predict the slow
 est relaxation time of the system and assess the suitability of a reacti
 on coordinate in capturing the slowest process. We will also propose a m
 ethod to coarse-grain MSM\, based on a variational principle\, that hold
 s for the slowest relaxation time\, and show that this has a simple inte
 rpretation\, for equilibrium dynamics governed by one-dimensional Smochu
 lowski equations\, in terms of mean first passage times between the coar
 se-grained states. This will be a virtual seminar. Today's meeting is ho
 sted at https://meet.jit.si/WCPMWindyMayMonday. Please join 5 minutes pr
 ior to the meeting time. To avoid background noise\, please ensure your 
 microphone is muted.
LOCATION:Virtual seminar
CATEGORIES:
LAST-MODIFIED:20200512T113017Z
ORGANIZER;CN=Sarah Jarratt:
END:VEVENT
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