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BEGIN:VEVENT
DTSTAMP:20260811T231338Z
DTSTART;VALUE=DATE-TIME:20180625T130000
DTEND;VALUE=DATE-TIME:20180625T140000
SUMMARY:Gareth Tribello (Belfast)
TZID:Europe/London
UID:20180625-8a17841b621f391b016225173f6f3247@warwick.ac.uk
CREATED:20180618T081805Z
DESCRIPTION:Variations on kernel density estimation Molecular dynamics me
 thodologies are now frequently used to shed light on the atomic scale me
 chanisms that underlie chemical and physical processes. For example mole
 cular dynamics has been used extensively to study phenomena such as crys
 tallisation\, the interfaces between different phases of a material and 
 nucleation. One of the most useful things we can extract from a molecula
 r dynamics simulation is the free energy as a function of some collectiv
 e variable or order parameter. This new energy landscape is useful becau
 se it provides us with quantitative understanding of the driving force a
 nd barriers to a process as a function of some coarse grained variables.
  Extracting this quantity from a simulation is often difficult\, however
 \, because of the limited sampling of phase space that we obtain when we
  perform unbiased molecular dynamics. For this reason there are thus a p
 lethora of so-called enhanced sampling algorithms that use a bias potent
 ial to force the system to sample more of phase space. Furthermore\, man
 y of these algorithms are implemented in the piece of software\, PLUMED\
 , that I and others develop [1]. When using enhanced sampling calculatio
 ns to calculate free energy surfaces it is important to remember that we
  are extracting statistical averages. It is thus important to quote erro
 r bars when reporting free energy surfaces. In the first part of my talk
  I will thus give a brief reminder as to how error bars are computed whe
 n running enhanced sampling calculations [2]. In the second part of my t
 alk I will discuss a method for calculating histograms that is known as 
 kernel density estimation. I will then provide a number of examples show
 ing how we have used this idea to analyse trajectories [3\,4] and to dev
 elop collective variables [5\,6\,7]. [1] www.plumed.org [2] Giovanni Bus
 si and I have recently written a chapter for an upcoming textbook on bio
 molecular simulations recently that discusses the issue of error bars an
 d WHAM. I am more than happy to share drafts of this work. [3] I. Gimond
 i\, G. A. Tribello\, M. Salvalaglio J. Chem. Phys. (2018) submitted [4] 
 E. Baldi\, M. Ceriotti and G. A Tribello J Phys Condens Matter (2017) 29
  445001 [5] J. Klug\, C. Triguero\, M. G. Del Popolo and G. A. Tribello 
 J. Phys. Chem. B (2018) accepted [6] F. Giberti\, G. A. Tribello and M. 
 Parrinello (2013) JCTC 9 2526 [7] G. Gobbo\, M. A. Bellucci\, G. A Tribe
 llo\, G. Ciccotti and B. L. Trout (2018) JCTC 14 959
LOCATION:D2.02
CATEGORIES:
LAST-MODIFIED:20180618T081805Z
ORGANIZER;CN=James Kermode:
END:VEVENT
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