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Maximum likelihood estimations of force and mobility from single short Brownian trajectories
Raphael Sarfati1, Jerzy Bławzdziewicz2, Eric R Dufresne3
1Department of Applied Physics, Yale University, New Haven, CT 06520, USA.
Soft Matter
|February 25, 2017
Abstract:
We describe a method to extract force and diffusion parameters from single trajectories of Brownian particles. The analysis, based on the principle of maximum likelihood, is well-suited for out-of-equilibrium trajectories, even when a limited amount of data is available and the dynamical parameters vary spatially. We substantiate this method with experimental and simulated data, and discuss its practical implementation, strengths, and limitations.

