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
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.
Long-range forces between bodies in active matter
A single non-spherical body placed in an active fluid generates currents. When two or more passive bodies are placed in an active fluid these currents lead to long-range interactions. Using a multipole expansion their leading-order behaviors will be characterized in terms of single-body properties. The interactions are showed to decay as a power law with the distance between the bodies, be anisotropic, and not obey an action-reaction principle. The interactions lead to rich dynamics of the bodies, illustrated by the spontaneous synchronized rotation of pinned non-chiral bodies and the formation of traveling bound pairs. The occurrence of these phenomena depends on tunable properties of the bodies, thus opening new possibilities for self-assembly mediated by active fluids.
Pattern Formation in Active Cytoskeletal Systems
Living cells rely on the self-organization mechanisms of cytoskeleton to adapt to their requirements. In processes such as cell division, or cellular motility rely on the controlled self-assembly and disassembly of well defined active cytoskeletal structures interacting with lipid membranes. One important and promising strategy to identify the underlying governing principles is to quantify the underlying physical processes in model systems mimicking functional units of living cell. Here I’ll present in vitro minimal model systems, which allow the identification of the ordering effects emerging in such collective systems. In a first part I will present recent results of a high density motility essay, how weak local interactions can be sensitively tuned to lead to different symmetries of the pattern forming system. In a second model system consisting of active microtubule and actin filament systems which show pattern formation resulting from topological constraints. I will discuss how a balance of local force exertion and tension generation results in shape transformations, blebbing, invagination or tethering of lipid membranes.
Microscopic efficiency sets the kinetics and structure of active fluids
In contrast with systems driven by an external field, the energy injection in active matter is local and independent for each particle, opening the possibility of a phase separation even with purely repulsive interactions. While such a phenomenon has been studied extensively, understanding how the microscopic energy fluxes control the emerging collective behavior, and its connection with entropy production [1, 2], has remained an elusive goal.
Based on methods of stochastic thermodynamics, we define a particle based efficiency as the proportion of injected power which effectively leads to collisional slowing down of the dynamics. We demonstrate that there exist generic relations between such an efficiency and transport properties quantified via the effective diffusion and mobility of an internal tracer. Moreover, we show that the spatial profile of efficiency controls the structure of a phase separated state by setting the form of the interface between dilute and dense phases. We also discuss how the instantaneous efficiency reveals failures in compact structures, such as fractures and moving defects.
These recent findings shed a new light on the control of active fluid properties by microscopic efficiency. It opens the door to the design of new active systems based on monitoring locally internal energy fluxes.