Swimming suppresses correlations in dilute suspensions of pusher microorganisms

Dataset

Abstract

Active matter exhibits various forms of non-equilibrium states in the absence of external forcing, including macroscopic steady-state currents. Such states are often too complex to be modelled from first principles and our understanding of their physics relies heavily on minimal models. These have mostly been studied in the case of “dry” active matter, where particle dynamics are dominated by friction with their surroundings. Significantly less is known about systems with long-range hydro- dynamic interactions that belong to “wet” active matter. Dilute suspensions of motile bacteria, modelled as self-propelled dipolar particles interacting solely through long-ranged hydrodynamic fields, are arguably the most studied example from this class of active systems. Their phenomenol- ogy is well-established: at sufficiently high density of bacteria, there appear large-scale vortices and jets comprising many individual organisms, forming a chaotic state commonly known as bac- terial turbulence. As revealed by computer simulations, below the onset of collective motion, the suspension exhibits very strong correlations between individual microswimmers stemming from the long-ranged nature of dipolar fields. Here we demonstrate that this phenomenology is captured by the minimal model of microswimmers. We develop a kinetic theory that goes beyond the com- monly used mean-field assumption, and explicitly takes into account such correlations. Notably, these can be computed exactly within our theory. We calculate the fluid velocity variance, spatial and temporal correlation functions, the fluid velocity spectrum, and the enhanced diffusivity of tracer particles. We find that correlations are suppressed by particle self-propulsion, although the mean-field behaviour is not restored even in the limit of very fast swimming. Our theory is not perturbative and is valid for any value of the micro-swimmer density below the onset of collective motion. This work constitutes a significant methodological advance and allows us to make qual- itative and quantitative predictions that can be directly compared to experiments and computer simulations of micro-swimmer suspensions.

Data Citation

Morozov, Alexander; Skultety, Viktor; Marenduzzo, Davide. (2020). Swimming suppresses correlations in dilute suspensions of pusher microorganisms, [software]. University of Edinburgh. School of Physics and Astronomy. https://doi.org/10.7488/ds/2894.
Date made available5 Aug 2020
PublisherEdinburgh DataShare

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