Systems governed by nonlinear equations of motion behave in ways that are qualitatively different from their linear counterparts. Nonlinearities lead to complex response to perturbations: energy, momentum, and other physical quantities can be redistributed among many different length and time scales, and the system can display chaos. But even though the behavior of such systems, such as turbulent fluid flow, can be extremely complicated, it is not random. Rather, nonlinear systems often show a high degree of spontaneous self-organization, with coherent macroscopic behavior emerging from the complex small-scale dynamics.
In the Ouellette lab, we study self-organization in a variety of complex systems, ranging from turbulent fluid flow to granular materials to collective motion in animal groups. In all cases, we aim to characterize the macroscopic behavior, understand its origin in the microscopic dynamics, and ultimately harness it for engineering applications. Most of our projects are experimental, though we also use numerical simulation and mathematical modeling when appropriate. We specialize in high-speed, detailed imaging and statistical analysis. Follow the links to the left for more information about specific projects.
Our work is currently supported by funds from the U.S. National Science Foundation and the Army Research Office.