TY - JOUR
T1 - Maximum likelihood estimations of force and mobility from single short Brownian trajectories
AU - Sarfati, Raphael
AU - Bławzdziewicz, Jerzy
AU - Dufresne, Eric R.
N1 - Funding Information:
This work was supported by the National Science Foundation (CBET 12-36086). We would like to thank Jason Merrill, Robert Style, and Larry Wilen for helpful discussions.
Publisher Copyright:
© The Royal Society of Chemistry.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85015219802&partnerID=8YFLogxK
U2 - 10.1039/c7sm00174f
DO - 10.1039/c7sm00174f
M3 - Article
C2 - 28233883
AN - SCOPUS:85015219802
SN - 1744-683X
VL - 13
SP - 2174
EP - 2180
JO - Soft Matter
JF - Soft Matter
IS - 11
ER -