Eric Sembrat's Test Bonanza

Cooperative groups often exhibit capabilities that exceed those of their individual members. On the other hand, collective actions may wash out crucial knowledge held out by individual group members. This talk will present the conflict between a group and the individuals that comprise it in the context of cooperative load retrieval by longhorn crazy ants. This behavior relies on the group to exert a large enough force to move the large load but also on the navigational capabilities of individual insects. 

We show how an ant group creates large scale coordination while preserving the influence of transiently informed individuals. Further, we show how emergent processes kick in when these individuals fail to supply the group with useful directions. This system provides an example of the way collective cognition simultaneously draws on all organizational levels of a complex biological ensemble.

We study the formation of the RbCs molecule by an intense laser pulse using nonlinear dynamics. The system is modeled by a two-degree-of-freedom rovibrational Hamiltonian, which includes the ground electronic potential energy curve of the diatomic molecule and the interaction of the molecular polarizability with the electric field of the laser. As the laser intensity increases, we observe that the formation probability first increases and then decreases after reaching a maximum.

We show that the analysis can be simplified to the investigation of the long-range interaction between the two atoms. We conclude that the formation is due to a very small change in the radial momentum of the dimer induced by the laser pulse. From this observation, we build a reduced one-dimensional model which allows us to derive an approximate expression of the formation probability as a function of the laser intensity.

Recent advances in camera sensor technology and the maturation of machine vision analysis pipelines now allow for recording bird flight trajectories in the field with high spatial and temporal precision, informing analyses of flight biomechanics and intraspecific interactions.

These include data on high speed, high-G maneuvers impossible to recreate in laboratory apparatus such as wind tunnels as well as simultaneous recordings of the position of > 1000 individuals in bird flocks.

Dr. Hedrick uses these data to explore predator-prey interactions on the wing, latency and flapping kinematics in intraspecific pursuits and comparisons of models and data for large bird flocks.

Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks -- the topology and edge weights -- determines how efficiently the networks perform their function. Yet, the set of tools that can characterize such a weighted cycle-rich architecture in a physically relevant, mathematically compact way is sparse. In order to fill this void, this seminar presents a new characterization that rests on an abstraction of the physical `tiling' in the case of a two dimensional network to an effective tiling of an abstract surface in space that the network may be thought to sit in.

 Generically these abstract surfaces are richer than the plane and upon sequential removal of the weakest links by edge weight, neighboring tiles merge and a tree characterizing this merging process results. The properties of this characteristic tree can provide the physical and topological data required to describe the architecture of the network and to build physical models.

This new algorithm can be used for automated phenotypic characterization of any weighted network whose structure is dominated by cycles, such as, for example, mammalian vasculature in the organs, the root networks of clonal colonies like quaking aspen, and the force networks in jammed granular matter. In particular this seminar will also present some progress in the analysis of both neurovasculature and force networks chains.​

Invited speakers:

Ravi Kane, Georgia Tech

Alberto Fernandez-Nieves, Georgia Tech

Eric Weeks, Emory University

Khalid Salaita, Emory University

The rest of the time will be allotted to SHORT presentations (3 minute “sound bites”) that are intended to give the audience a flavor for the research topics and the techniques used to address the research problems discussed. We hope and expect that students will attend whether or not their faculty adviser can attend.

The ability to reconfigure elementary building blocks from one structure to another is key to many biological system. Bringing the intrinsic adaptability of biological systems to traditional synthetic materials is currently one of the biggest scientific challenges in material engineering. Here we introduce a new design concept for the experimental realization of self-assembling systems with built-in shape-shifting elements.

We demonstrate that dewetting forces between an oil phase and solid colloidal substrates can be exploited to engineer shape-shifting particles whose geometry can be changed on demand by a chemical or optical signal. We find this approach to be quite general and applicable to a broad spectrum of materials, including polymers, semiconductors and magnetic materials. 

Jennifer Zallen is an HHMI Investigator at Sloan Kettering Institute. Her lab uses multidisciplinary approaches from cell and developmental biology, physics, engineering, and computer science to study how tissue architecture is dynamically remodeled throughout development.  A major morphogenetic event during the development of the embryo is the elongation of the head-to-tail body axis, a process that requires rapid and coordinated movements of hundreds of cells. 

Her lab identified the force-generating machinery that drives polarized cell movements during axis elongation in Drosophila, and discovered that these movements are systematically oriented by a global positional code that involves an ancient family of receptors that are widely used for pathogen recognition by the innate immune system. These studies elucidate general principles that link cellular-level asymmetries and mechanical forces to global tissue reorganization.

The diffusion of lipids and proteins within membranes are crucial to a variety of biological processes. With proper physical understanding, the diffusion coefficient gives information about the size, oligomerization, and local environment. It also serves as a standard test of simulation parameters.

We will discuss the statistics involved in calculating diffusion coefficients from both simulation and single-molecule experiments. Getting this right also gives us a nice way to quantify correlated motions in both simulations and experiments. Meanwhile, simulations are typically performed in periodic boundary conditions. We find that these conditions can cause typical simulations to underestimate experiment by a factor of 3 or more.

We will review the underpinning of the micro-canonical ensemble and the more refined (and explicitly quantum) "Eigenstate Thermalization Hypothesis". We will then find and apply a simple corollary of these to analyze the evolution of a liquid upon supercooling to form a structural glass. Simple theoretical considerations lead to predictions for general properties of supercooled liquids. Amongst other things, a collapse of the viscosity of glass formers is predicted from this theory. This collapse indeed occurs over 16 decades of relaxation times for all known types of glass formers.