Archives: Events

Using a stochastic field theory to understand active colloidal suspensions

Even without external forcing active systems are out of equilibrium, which gives rise to interesting properties in both small and large concentrations of the particles. These properties have been observed in experiments as well as simulation/modeling approaches. It is important to understand how hydrodynamic interactions between active colloids cause and/or alter the suspension properties including enhanced transport and mixing. One of the most successful approaches has been a mean field theory. However, in some situations the mean field theory makes predictions that differ significantly from experiments and direct (agent or particle based) simulations. There are also some quantities that cannot be calculated by the mean field theory. We will describe our new approach which uses a stochastic field to overcome the limitations of the mean field assumption. It allows us to calculate how interactions between organisms alter the correlations and mixing even in conditions where there is no large-scale group behavior.

Toward a “Thermodynamics” of Collective Behavior

Aggregations of social animals are beautiful examples of self-organized behavior far from equilibrium. Understanding these systems, however, has proved to be quite challenging. Determining the rules of interaction from empirical measurements of animals is a difficult inverse problem. Thus, researchers tend to focus on the macroscopic behavior of the group instead. Because so many of these systems display large-scale ordered patterns, it has become the norm in modeling to focus on this order. Large-scale pattern alone, however, is not sufficient to characterize the dynamics of animal aggregations, and does not provide a stringent enough condition to benchmark models. Instead, I will argue that we should borrow ideas from materials characterization to describe the macroscopic state of an animal group in terms of its response to external stimuli. I will illustrate these ideas with recent experiments on swarms of the non-biting midge Chironomus riparius, where we have developed methods to apply controlled perturbations and measure the detailed swarm response. Our results allow us to begin to describe swarms in terms of state variables and response functions, bringing them into the purview of theories of active matter, and point towards new ways of characterizing and hopefully comparing collective behavior in animal groups.

Experimental investigations of collective motion of self-propelled particles

Using minimal models described by simple rules like the Vicsek model, collective motion of self-propelled particles is well studied. Recently, we found that the predicted long-range orderd phase with the giant number flucuations exists in the real world using E. coli (D. Nishiguchi, KHN, et al. 2017), which indicates that unified descriptions of collective motion in the real world actually exists.

The particles in the Vicsek model change their direction randomly. However, there are various kinds of self-propelled particle that keeps its rotation rate for a long time such as an E. coli close to wall and a mycoplasma on a glass plate. Using an agent-based model like the Vicsek model, we elucidated the role of memory of rotation rate in collective motion of self-propelled particles. We found that the collective motions observed using our model were formed microtubules running on a glass grafted by dyneins (Y. Sumino, KHN, et al. 2012, KHN, et al. 2015). The recent results of experiments using C. elegans on a substrate, which keeps its rotation rate for a while, were also well-reproduced by our model. These results indicate that there exist unified descriptions of rotating self-propelled particles.