Gaussian memory in kinematic matrix theory for self-propellers

Modulating drift dynamics of circle swimmers by periodic potentials

We propose a method to modulate the drifting motion of overdamped circle swimmers in steady fluid flows by means of static sinusoidal potentials. Using Langevin formalism, we study drift velocity as a function of potential strength and wavelength with and without diffusional motion. Drift velocity is essentially quantized without diffusion, but in the presence of noise, the displacement per cycle has a continuous range. As a function of dimensionless potential wave number, domains of damped oscillatory and plateau regimes are observed in the drift velocity diagram. At weak potential and fluid velocity less than powered velocity, there is also a regime where drift velocity exceeds the fluid velocity. Methods based on these results can be used to separate biological and artificial circle swimmers based on their dynamical properties.

Memory effects in spiral diffusion of rotary self-propellers

The coupling of deterministic rotary motion and stochastic orientational diffusion of a self-propeller leads to a spiral trajectory of the expected displacement. We extend our former analysis of spiral diffusion [Phys. Rev. E 94, 030601(R) (2016)10.1103/PhysRevE.94.030601] in the white-noise limit to a more realistic scenario of stochastic noise with Gaussian memory and orientational fluctuations driven by an Ornstein-Uhlenbeck process. A variety of dynamical regimes including crossovers from ballistic to diffusive to ballistic in the angular dynamics are determined by the inertial timescale, orientational diffusivity, and angular speed.

How to connect time-lapse recorded trajectories of motile microorganisms with dynamical models in continuous time

We provide a tool for data-driven modeling of motility, data being time-lapse recorded trajectories. Several mathematical properties of a model to be found can be gleaned from appropriate model-independent experimental statistics, if one understands how such statistics are distorted by the finite sampling frequency of time-lapse recording, by experimental errors on recorded positions, and by conditional averaging. We give exact analytical expressions for these effects in the simplest possible model for persistent random motion, the Ornstein-Uhlenbeck process. Then we describe those aspects of these effects that are valid for any reasonable model for persistent random motion. Our findings are illustrated with experimental data and Monte Carlo simulations.

Spiral diffusion of rotating self-propellers with stochastic perturbation

Translationally diffusive behavior arising from the combination of orientational diffusion and powered motion at microscopic scales is a known phenomenon, but the peculiarities of the evolution of expected position conditioned on initial position and orientation have been neglected. A theory is given of the spiral motion of the mean trajectory depending upon propulsion speed, angular velocity, orientational diffusion, and rate of random chirality reversal. We demonstrate the experimental accessibility of this effect using both tadpole-like and Janus sphere dimer rotating motors. Sensitivity of the mean trajectory to the kinematic parameters suggest that it may be a useful way to determine those parameters.

Diffusion of eccentric microswimmers

We model the two-dimensional diffusive dynamics of an eccentric artificial microswimmer in a highly viscous medium. We assume that the swimmer's propulsion results from an effective force applied to a center distinct from its center of mass, both centers resting on a body's axis parallel to its average self-propulsion velocity. Moreover, we allow for angular fluctuations of the velocity about the body's axis. We prove, both analytically and numerically, that the ensuing active diffusion of the swimmer is suppressed to an extent that strongly depends on the model parameters. In particular, the active diffusion constant undergoes a transition from a quadratic to a linear dependence on the self-propulsion speed, with practical consequences on the interpretation of the experimental data. Finally, we extend our model to describe the diffusion of chiral eccentric swimmers.

Nonholonomic diffusion of a stochastic sled

A sled is a stylized mechanical model of a system which is constrained to move in space in a specific orientation, i.e., in the direction of the runners of the sled or a blade. The negation of motion transverse to the runners renders the sled a nonholonomic mechanical system. In this paper we report on the unexpected and fascinating richness of the dynamics of such a sled if it is subject to random forces. Specifically we show that the ensuing random dynamics is characterized by relatively smooth sections of motion interspersed by episodes of persistent tumbling (change of orientation) and sharp reversals resembling the random walks of bacterial cells. In the presence of self-propulsion, the diffusivity of the sled can be enhanced and suppressed depending on the directionality and strength of the propulsive force.

Self-consistent nonlocal feedback theory for electrocatalytic swimmers with heterogeneous surface chemical kinetics

We present a self-consistent nonlocal feedback theory for the phoretic propulsion mechanisms of electrocatalytic micromotors or nanomotors. These swimmers, such as bimetallic platinum and gold rods catalyzing decomposition of hydrogen peroxide in aqueous solution, have received considerable theoretical attention. In contrast, the heterogeneous electrochemical processes with nonlocal feedback that are the actual "engines" of such motors are relatively neglected. We present a flexible approach to these processes using bias potential as a control parameter field and a locally-open-circuit reference state, carried through in detail for a spherical motor. While the phenomenological flavor makes meaningful contact with experiment easier, required inputs can also conceivably come from, e.g., Frumkin-Butler-Volmer kinetics. Previously obtained results are recovered in the weak-heterogeneity limit and improved small-basis approximations tailored to structural heterogeneity are presented. Under the assumption of weak inhomogeneity, a scaling form is deduced for motor speed as a function of fuel concentration and swimmer size. We argue that this form should be robust and demonstrate a good fit to experimental data.