Pantheon SEMPARIS Le serveur des séminaires parisiens Paris

Statut Confirmé
Domaines physics
Date Mardi 9 Octobre 2018
Heure 11:00
Institut LPTMS
Salle LPTMS, salle 201, 2ème étage, Bât 100, Campus d'Orsay
Nom de l'orateur Ronceray
Prenom de l'orateur Pierre
Addresse email de l'orateur
Institution de l'orateur Princeton Center for Theoretical Science
Titre Learning force fields from stochastic trajectories
Résumé From nanometer-scale proteins to micron-scale colloidal particles, particles in biological and soft matter systems undergo Brownian dynamics: their deterministic motion due to external forces and interactions competes with the random diffusion 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 inspecting microscopy observations of the system’s trajectory is a hard problem, for two reasons. First, there needs to be enough information about the force available in the trajectory: the effect of the force field becomes apparent only after a long enough observation time. Second, one needs a practical method to extract that information and reconstruct the force field, which is challenging for force fields with a spatial structure, in particular in the presence of measurement noise. Here we address these two problems for steady-state Brownian trajectories. We first give a quantitative meaning to the information contained in a trajectory, and show how it limits force inference. We then propose a practical procedure to optimally use this information to reconstruct the force field by decomposing it into moments. Using simple model stochastic processes, we demonstrate that our method permits a quantitative evaluation of phase space forces and currents, circulation, and entropy production with a minimal amount of data.
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