Gaussian Memory in Kinematic Matrix Theory for Self-Propellers
Abstract
We extend the kinematic matrix ("kinematrix") formalism [Phys. Rev. E 89, 062304 (2014)], which via simple matrix algebra accesses ensemble properties of self-propellers influenced by uncorrelated noise, to treat Gaussian correlated noises. This extension brings into reach many real-world biological and biomimetic self-propellers for which inertia is significant. Applying the formalism, we analyze in detail ensemble behaviors of a 2D self-propeller with velocity fluctuations and orientation evolution driven by an Ornstein-Uhlenbeck process. On the basis of exact results, a variety of dynamical regimes determined by the inertial, speed-fluctuation, orientational diffusion, and emergent disorientation time scales are delineated and discussed.
Cite
@article{arxiv.1409.2955,
title = {Gaussian Memory in Kinematic Matrix Theory for Self-Propellers},
author = {Amir Nourhani and Vincent H. Crespi and Paul E. Lammert},
journal= {arXiv preprint arXiv:1409.2955},
year = {2015}
}
Comments
8 pages, 4 figures