The Physics of Flocking
Location: Wheeler Opera House
Location: Meadows, Doerr-Hosier Center.
We have received precise guidelines for the dinner:
Aspen Center for Physics – Banquet Dinner Guidelines
- Dinners will be scheduled 30 minutes after the final session
hosted at the Aspen Center for Physics unless otherwise
requested by the coordinator.
- Participants should be aware that if they arrive more than 30
minutes after the dinner service begins, The Aspen Meadows
cannot guarantee that we will be able to accommodate.
- Participants must sign up and pay by Monday at 12:00pm
(noon) of the dinners, at that point they will be considered
- The Aspen Meadows will only be able to accommodate
additional guests counts up to 10% above those who paid in
advance. These guests should be prepared to pay at the time of
service. Due to the recent renovation, we do not at this time
have an in house restaurant.
- Any guests who we are unable to accommodate may order off of
the ‘In Room Dining’ menu located in their guest hotel rooms.
Location: Wheeler Opera House
Location: Aspen Center for Physics – Smart Hall
- Wylie Ahmed, Soft, Living, and Active Matter Laboratory
- Joseph Albert, Reynolds vs. Peclet – Finite acceleration in the Stokes regime from slowly relaxing gradients
- Laura Alvarez, Programmable assembly of hybrid colloidal microswimmers
- Antoine Aubret, Dynamical Self-Assembly of Self-Spinning Microgears
- Yongjoo Baek, Negative mobility of passive bodies in active fluids
- Oliver Baeumchen, Light-Switchable Adhesion, Biofilm Formation and Collective Effects of Microalgal Suspensions
- Peter Foster, A Hierarchy of Instabilities in an Active Material
- Yohsuker Fukai, Large-scale flow in electroconvection of cholesteric liquid crystal
- Tetsuya Hiraiwa, Theory on chemotactic migration of eukaryotic cells
- Theresa Jakuszeit, Dynamics of chemotactic and chemokinetic bacterial populations
- Ah-Young Jee, Enzymes and other proteins using super-resolution fluctuation microscopy
- Airi N. Kato, Reciprocating motion and the net locomotion of the Quincke rollers under AC fields
- Jaideep Katuri, Artificial micro-swimmers respond to external cues
- Sofia Magkiriadou, A colloidal spinner fluid
- Christopher Miles, Unstable self-stretching and invasion of active matter in a viscous fluid
- Janna Nawroth, The Hawaiian bobtail squid: A model system for flow functions of ciliated surfaces
- Hyuk Kyu Pak, An information-driven Brownian motor achieved experimentally by asymmetric cooling
- Praneet Prakash, Dynamics of payload carrying bacteria
- Geet Raju, Active sedimentation equilibrium of Quincke rollers
- Jeroen Rodenburg, Van’t Hoff’s law for active suspensions: the role of the solvent chemical potential
- Suraj Shankar, Irreversibility in an active gas
- Sakurako Tanida, The effects of volume exclusion on collective motion of microtubules
- Erik Verriest, Graceful Gait Transitions via Homotopy of Periodic Behaviors
- Hiroki Yamaguchi, Breakdown of tissue homeostasis and stochastic Fisher waves
- Ryoichi Yamamoto, Particle-based model for crawling and proliferating cells with contact inhibitions
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.