Single-Trajectory Characterization of Active Swimmers in a Flow

TL;DR

This paper introduces a maximum likelihood method to analyze individual trajectories of active swimmers, enabling accurate estimation of their physical properties like rotational diffusion and aspect ratio from single-particle data, validated through simulations.

Contribution

The paper presents a novel maximum likelihood approach for characterizing active particles from single trajectories, applicable in diverse flow conditions and experimental settings.

Findings

Accurately estimates rotational diffusion coefficients.

Provides reliable aspect ratio measurements.

Validated with simulations in various flow regimes.

Abstract

We develop a maximum likelihood method to infer relevant physical properties of elongated active particles. Using individual trajectories of advected swimmers as input, we are able to accurately determine their rotational diffusion coefficients and an effective measure of their aspect ratio, also providing reliable estimators for the uncertainties of such quantities. We validate our theoretical construction using numerically generated active trajectories upon no-flow, simple shear, and Poiseuille flow, with excellent results. Being designed to rely on single-particle data, our method eases applications in experimental conditions where swimmers exhibit a strong morphological diversity. We briefly discuss some of such ongoing experimental applications, specifically, in the characterization of swimming E.coli in a flow.