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Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior

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Published on: January 31, 2020

Non-normal tracer diffusion from stirring by swimming microorganisms.

B Eckhardt¹, S Zammert

¹Fachbereich Physik and LOEWE Zentrum Synthetische Mikrobiologie, Philipps-Universität Marburg, D-35032, Marburg, Germany.

The European Physical Journal. E, Soft Matter

|October 12, 2012

Summary

This summary is machine-generated.

Passive tracer distributions in active swimmer-stirred fluids exhibit non-Gaussian behavior. Continuous time random walks with specific trapping and step size distributions explain these experimental observations.

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Area of Science:

Soft Matter Physics
Statistical Mechanics
Fluid Dynamics

Background:

Experimental studies show non-Gaussian tracer distributions in fluids stirred by active swimmers.
Understanding these distributions is key to characterizing complex fluid dynamics.

Purpose of the Study:

Analyze experimentally observed non-Gaussian tracer distributions using continuous time random walks (CTRWs).
Relate CTRRW parameters to observed phenomena and determine relevant exponents.

Main Methods:

Modeled tracer movement using continuous time random walks.
Characterized walks by trapping time distribution ψ(τ) ~ τ^(-1-α) and step size distribution p(Δx) ~ (Δx)^(-2-β).
Investigated the relationship β = 2α for observed behavior.

Main Results:

Derived the condition β = 2α to match the experimentally observed mean squared displacement 〈x²〉 ~ t.
The resulting distribution function is non-Gaussian with exponential tails.
The model's distribution shape closely matches experimental observations.

Conclusions:

Continuous time random walks provide a robust framework for understanding non-Gaussian tracer transport in active fluids.
The determined exponent relationship (β = 2α) successfully explains experimental findings.
This approach allows for the quantitative determination of system exponents from observed distributions.