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UID:d346de495a1948a65d37e85e2336faaf
CATEGORIES:Mathematical Physics Seminar
CREATED:20260707T123652
SUMMARY:Webinar: Christopher Jarzynski - Estimating free energy differences with virtually escorted trajectories
LOCATION:Zoom
DESCRIPTION:<p style="text-align: center;"><strong>Christopher Jarzynski</strong> <stro
 ng>– University of Maryland</strong></p><p style="text-align: center;"><str
 ong>Wednesday,&nbsp;July 29,&nbsp;2026</strong></p><p style="text-align: ce
 nter;"><strong>Zoom opens: 10:30AM EDT</strong></p><p style="text-align: ce
 nter;"><strong>Seminar begins: 10:45AM EDT</strong></p><p style="text-align
 : center;"><strong>Estimating free energy differences with virtually escort
 ed trajectories</strong></p><p>The convergence of numerical free energy est
 imation methods can be accelerated using artificial fields that “escort” si
 mulated trajectories along near-equilibrium paths.&nbsp; Unfortunately, des
 igning such fields is not easy.&nbsp; Taking a cue from the mathematics beh
 ind diffusion models – a class of generative models in machine learning – w
 e introduce a method based on virtual escorting.&nbsp; This method adopts a
  post-processing approach.&nbsp; Given a fixed set of nonequilibrium trajec
 tories, a parameter-dependent virtual escorting field is constructed, possi
 bly using a neural network.&nbsp; This field is used in combination with th
 e trajectories to produce an estimate of the desired free energy difference
 .&nbsp; The parameters are then adjusted to optimize the convergence of the
  estimate.&nbsp; I will describe the method, and will discuss conditions un
 der which it produces a zero-variance estimator of the free energy differen
 ce.</p>
DTSTAMP:20260827T094727
DTSTART;TZID=America/New_York:20260729T104500
DTEND;TZID=America/New_York:20260729T120000
SEQUENCE:0
TRANSP:OPAQUE
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