Fluid heterogeneity detection based on the asymptotic distribution of the time-averaged mean squared displacement in single particle tracking experiments

Abstract

A tracer particle is called anomalously diffusive if its mean squared displacement grows approximately as ${\sigma }^2{t}^{\alpha }$ as a function of time $t$ for some constant ${\sigma }^2$, where the diffusion exponent satisfies $\alpha \ne 1$. In this article, we use recent results on the asymptotic distribution of the time-averaged mean squared displacement (Didier and Zhang (2017)) to construct statistical tests for detecting physical heterogeneity in viscoelastic fluid samples starting from one or multiple observed anomalously diffusive paths. The methods are asymptotically valid for the range $0<\alpha <3/2$ and involve a mathematical characterization of time-averaged mean squared displacement bias and the effect of correlated disturbance errors. The assumptions on particle motion cover a broad family of fractional Gaussian processes, including fractional Brownian motion and many fractional instances of the generalized Langevin equation framework. We apply the proposed methods in experimental data from treated $P.aeruginosa$ biofilms generated by the collaboration of the Hill and Schoenfisch Labs at UNC-Chapel Hill.

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Cited by in corpus (1)

• Asymptotic theory for the detection of mixing in anomalous diffusion