Maximum likelihood estimations of force and mobility from single short Brownian trajectories

Raphael Sarfati; Jerzy Bławzdziewicz; Eric R. Dufresne

doi:10.1039/c7sm00174f

Maximum likelihood estimations of force and mobility from single short Brownian trajectories

Raphael Sarfati, Jerzy Bławzdziewicz, Eric R. Dufresne

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

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.

Original language	English
Pages (from-to)	2174-2180
Number of pages	7
Journal	Soft Matter
Volume	13
Issue number	11
DOIs	https://doi.org/10.1039/c7sm00174f
State	Published - 2017

Access to Document

10.1039/c7sm00174f

Fingerprint Dive into the research topics of 'Maximum likelihood estimations of force and mobility from single short Brownian trajectories'. Together they form a unique fingerprint.

Cite this

@article{061e4640464d4811b79b262c71392d76,

title = "Maximum likelihood estimations of force and mobility from single short Brownian trajectories",

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.",

author = "Raphael Sarfati and Jerzy B{\l}awzdziewicz and Dufresne, {Eric R.}",

year = "2017",

doi = "10.1039/c7sm00174f",

language = "English",

volume = "13",

pages = "2174--2180",

journal = "Soft Matter",

issn = "1744-683X",

number = "11",

}

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.

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

VL - 13

SP - 2174

EP - 2180

JO - Soft Matter

JF - Soft Matter

SN - 1744-683X

IS - 11

ER -