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TZID:Europe/Paris
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BEGIN:VEVENT
UID:0-621@lptms.universite-paris-saclay.fr
DTSTART:20181009T110000Z
DTEND:20181009T120000Z
DTSTAMP:20180903T103128Z
URL:http://www.lptms.universite-paris-saclay.fr/seminars/seminaire-du-lptm
 s-pierre-ronceray/
SUMMARY:Séminaire du LPTMS: Pierre Ronceray - LPTMS\, salle 201\, 2ème é
 tage\, Bât 100\, Campus d'Orsay - 9 Oct 18 11:00
DESCRIPTION:Learning force fields from stochastic trajectories\nPierre Ronc
 eray (Princeton Center for Theoretical Science\, USA)\nFrom nanometer-scal
 e proteins to micron-scale colloidal particles\, particles in biological a
 nd soft matter systems undergo Brownian dynamics: their deterministic moti
 on due to external forces and interactions competes with the random diffus
 ion due to thermal noise. In the absence of forces\, all trajectories look
  alike: the key information characterizing the system's dynamics thus lies
  in its force field. However\, reconstructing the force field by inspectin
 g microscopy observations of the system's trajectory is a hard problem\, f
 or two reasons. First\, there needs to be enough information about the for
 ce available in the trajectory: the effect of the force field becomes appa
 rent only after a long enough observation time. Second\, one needs a pract
 ical method to extract that information and reconstruct the force field\, 
 which is challenging for force fields with a spatial structure\, in partic
 ular in the presence of measurement noise. Here we address these two probl
 ems for steady-state Brownian trajectories. We first give a quantitative m
 eaning to the information contained in a trajectory\, and show how it limi
 ts force inference. We then propose a practical procedure to optimally use
  this information to reconstruct the force field by decomposing it into mo
 ments. Using simple model stochastic processes\, we demonstrate that our m
 ethod permits a quantitative evaluation of phase space forces and currents
 \, circulation\, and entropy production with a minimal amount of data.
CATEGORIES:seminars
LOCATION:LPTMS\, salle 201\, 2ème étage\, Bât 100\, Campus d'Orsay\, 15 
 Rue Georges Clemenceau\, Orsay\, 91405\, France
GEO:48.698185;2.181768
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=15 Rue Georges Clemenceau\,
  Orsay\, 91405\, France;X-APPLE-RADIUS=100;X-TITLE=LPTMS\, salle 201\, 2è
 me étage\, Bât 100\, Campus d'Orsay:geo:48.698185,2.181768
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