I will give an overview of properties, and analyses of those properties, of real quasi-two-dimensional colloid assemblies, with a view to identifying differences between the predictions of the quasi-two-dimensional and two-dimensional analyses.

Measurements of the microstructure commensurate with the viscosity and normal stress differences in shearing colloidal suspensions provides an understanding of how to control the viscosity, shear thinning, and shear thickening rheological behavior typical of concentrated dispersions. In this presentation, I will review some of the experimental methods and key results concerning the micromechanics of colloidal suspension rheology. In particular, colloidal and nanoparticle dispersions can exhibit shear thickening, which is an active area of research with consequences in the materials and chemical industries, as well as an opportunity to engineer novel energy adsorbing materials. A fundamental understanding of shear thickening has been achieved through a combination of model system synthesis, rheological, rheo-optical and rheo-small angle neutron scattering (SANS) measurements, as well as simulation and theory. In particular, the shear-induced self-organization of .hydroclusters. (transient colloid concentration fluctuations) as predicted by Stokesian Dynamics simulations are measured and connected to the suspension rheology. The onset of shear thickening is demonstrated to be understood as a balance of convective, colloidal and hydrodynamic forces and their associated timescales. The limits of shear thickening behavior are also explored at extreme shear rates and stresses, where particle material properties come into play. Although many applications of concentrated suspensions are hindered by shear thickening behavior, novel materials have been developed around shear thickening fluids (STFs). Ballistic, stab and impact resistant flexible composite materials are synthesized from colloidal & nanoparticle shear thickening fluids for applications as protective materials. The rheological investigations and micromechanical modeling serve as a framework for the rational design of STF-based materials to meet specific performance requirements not easily achieved with more conventional materials, as will be discussed. (Phys. Today, Oct. 2009, p. 27-32)

The history of quantum-mechanical entanglement over the last century is a fascinating example of how scientific knowledge actually proceeds. Personalities and personal passions (scientific and otherwise) sometimes hinder and sometimes even help the progress of human knowledge. Louisa Gilder is the author of The Age of Entanglement, which was named one of only five science books on the New York Times 100 Notable Books of 2009, as well as receiving enthusiastic reviews in Science, Nature, American Journal of Physics, and American Scientist.

DNA is a versatile tool for directing the controlled self-assembly of nanoscopic and microscopic objects. The interactions between microspheres due to the hybridization of DNA strands grafted to their surface have been measured and can be modeled in detail, using well-known polymer physics and DNA thermodynamics. Knowledge of the potential, in turn, enables the exploration of the complex phase diagram and self-assembly kinetics in simulation. Experimentally, these system readily form colloidal crystals having a diverse range of symmetries, at least at high densities of long grafted DNA strands, and at temperatures where the binding is reversible. For interactions that favor alloying between two same-sized colloidal species, our experimental observations compare favorably to a simulation framework that predicts the equilibrium phase behavior, crystal growth kinetics and solid-solid transitions. We will discuss the crystallography of the novel alloy structures formed and address how particle size and heterogeneity affect nucleation and growth rates.

Spin systems are natural building blocks for quantum devices. I will describe our various approaches to building small spin-based quantum processors with potential applications as sensors and special purpose quantum simulators. I hope to convince you that non-trivial quantum processors are available today.

We use an electrical method and high-speed imaging to provide a detailed description of coalescence near the moment of contact, t_0. We observe signatures both before and after t_0 that indicate whether the intervening gas layer has deformed the drops near their contact region. At sufficiently slow approach speed, the drops coalesce as spheres but with an unexpectedly late crossover time between the initial viscously-dominated regime and the subsequent inertial regime. By changing the liquid viscosity over two orders of magnitude, we identify the dominant scales in the problem. We argue that the late crossover, not accounted for in the theory, is due to the flow field in the liquid and a previously unappreciated length-scale in the drop geometry.

Cold Fermionic superfluid gases have brought together a number of physics sub-disciplines ranging from atomic molecular and optical (AMO) to condensed matter and finally also particle (ie., quark-gluon plasma) physics as well. This talk will emphasize this unique inter-disciplinarity and will summarize the almost heroic accomplishments (since 2003) of the experimental AMO community in characterizing these ultracold Fermi gases. Most notable are the development of new tools which have close analogies with condensed matter probes such as photoemission, transport and scattering. With these analogue probes in hand, we end by presenting the case that these ultracold Fermi superfluids may be also be a laboratory for learning about the high Tc superconductors. In this context we discuss the observation of pseudogap effects in the cold gases which are central to our understanding of the cuprates. Finally, we address a central paradox in the cuprates, the so-called "two gap" behavior and show how it has a natural counterpart in the cold gases.

Many interesting phenomena occur in material structures that are poised between rigid and flexible. In this talk, we describe the modern theory of rigidity and show how it can be used to analyze networks of constraints. These results can be used as input to geometrical simulation, where the various rigid parts of a system are moved, while maintaining all the constraints; both equalities and inequalities. This approach is applied to zeolites that are important for cracking petroleum, manganites that exhibit colossal magnetoresistance, and proteins where flexibility is often associated with function.

Soft and biological materials often exhibit disordered and heterogeneous microstructure. In most cases, the transmission and distribution of stresses through these complex materials reflects their inherent heterogeneity. We are developing a set of techniques that provide the ability to apply to quantify the connection between microstructure and local stresses. We subject soft and biological materials to precise deformations while measuring real space information about the distribution and redistribution of stress.

Using our custom confocal rheometer platform we can determine the role of shear stress in a variety of materials. First, I will describe our recent results on the nonlinear rheology of in vitro collagen networks. We apply precisely controlled shear strains to collagen networks that are adhered to a thin elastic polyacrylamide gel substrate embedded with fiduciary markers. By utilizing a modified version of traction force microscopy we can calculate the distribution of forces as a function of the applied strain. We find that the signatures of yielding in these materials follow a universal form. Second, I will discuss how the application of a cyclic load can determine the mechanical strength of a biopolymer system. We observe that when actin networks are cyclicly strained, they either work harden, or soften depending on the specifics of the cross-linking protein.

In modern biology, an important challenge is to link biophysical, genomic, and evolutionary aspects of an organism's molecular functions. As an example, we show how empirical fitness landscapes for gene regulation can be inferred from the thermodynamics of protein-DNA binding and from sequence data of genomic binding sites. This example addresses some general questions: How do biophysical constraints shape molecular evolution? When does this process take place in a static fitness landscape, and when is it driven by a dynamic fitness seascape? We show that the nonequilibrium fluctuations of evolutionary processes and of thermodynamic systems have strikingly analogous statistical principles - and challenging differences.

Neuroscience has advanced substantially in recent decades and today, new technologies enable us today, to monitor the neural activity of many neurons simultaneously. Quantitative approaches to understanding the main output of the brain, i.e., behavior, lag far behind. In my talk, I will attempt to explain why echolocating bats provide an excellent animal model for quantitative - computational studies of natural animal behavior.

Echolocating bats perceive their surroundings acoustically. They repetitively emit ultrasonic sonar signals and analyze the returning echoes in order to orient themselves in space and acquire food in complete darkness. Natural echoes compose a major part of the bat's sensory world, and have probably played a key evolutionary role in shaping the design of the bat's echolocation system and the auditory computations in the bat brain. However, the statistics of natural complex echoes and how bats utilize them are poorly understood. In the first part of the talk I will focus on natural stimulus statistics in the auditory modality (statistics of echoes) and the ability of bats to classify them. I will discuss a machine-learning based algorithm that we use to make behavioral predictions.

In the second part of the talk I will present a novel and surprising behavioral strategy that we found to be used by Egyptian fruit bats, which we show is optimal for localizing and tracking a stimulus. This strategy consists of placing the maximal slope of the sonar beam, which is most sensitive to changes in target location onto the target. Moreover, experiments under two conditions of signal-to-noise ratio (SNR) reveal that bats choose to use this "slope strategy" in high-SNR conditions, but use an "optimal-SNR strategy" (placing the peak of the sonar beam onto the target) under low-SNR conditions. We suggest that this tradeoff between SNR and localization is fundamental to sensory systems in general, and is probably relevant for other modalities and organisms.

The 20th Century has seen a notable temperature rise, generally attributed to the greenhouse effect of anthropogenic gases, and a future "business as usual" policy is generally believed to be catastrophic. I will show, however, that the story is not that simple. I will address the following questions,all of which have a far from trivial and often surprising answer: How large is the greenhouse effect? Could some of the temperature rise be natural and not anthropogenic? If so, what is this natural driver? How sensitive really is Earth's climate? What should we expect in the future? How effective will the implementation of a cap and trade agreement be?

The chemotaxis network of bacteria such as E. coli is remarkable for its sensitivity to minute relative changes in chemical concentrations in the environment. Indeed, E. coli cells can detect concentration changes corresponding to only ~3 molecules in the volume of a cell. Much of this acute sensitivity can be traced to the collective behavior of teams of chemoreceptors on the cell surface. Instead of receptors switching individually between active and inactive configurations, teams of 6-20 receptors switch on and off, and bind or unbind ligand, collectively. Similar to the binding and unbinding of oxygen molecules by tetramers of hemoglobin, the result is a sigmoidal binding curve. Coupled with a system for adaptation that tunes the operating point to the steep region of this sigmoidal curve, the advantage for chemotaxis is gain . i.e., small relative changes in chemical concentrations are transduced into large relative changes in signaling activity (specifically, the rate of phosphorylation of the response regulator CheY). However, something is troubling about this simple explanation: in addition to providing gain, the coupling of receptors into teams also increases noise, and the net result is a decrease in the signal-to-noise ratio of the network. Why then are chemoreceptors observed to form cooperative teams? We present a novel hypothesis that the run-and-tumble chemotactic strategy of bacteria leads to a .noise threshold., below which noise does not significantly decrease chemotactic velocity, but above which noise dramatically decreases this velocity.

All organisms rely on noisy molecular recognition to convey, process and store information. This stochastic biophysical setting poses a tough challenge: how to construct information processing systems that are efficient and economical yet error-resilient? I will review recent results that reveal generic design principles of molecular information systems. This biological design problem turns out to be equivalent to the statistical physics of stochastic maps and optimization processes. The examples considered range from molecular codes through molecular recognition and homologous recombination (a crucial mechanism of sexual reproduction that yields genetic diversity) to the spatial organization of chromosomes in the cell nucleus.

Measurements of the microstructure commensurate with the viscosity and normal stress differences in shearing colloidal suspensions provides an understanding of how to control the viscosity, shear thinning, and shear thickening rheological behavior typical of concentrated dispersions. In this presentation, I will review some of the experimental methods and key results concerning the micromechanics of colloidal suspension rheology. In particular, colloidal and nanoparticle dispersions can exhibit shear thickening, which is an active area of research with consequences in the materials and chemical industries, as well as an opportunity to engineer novel energy adsorbing materials. A fundamental understanding of shear thickening has been achieved through a combination of model system synthesis, rheological, rheo-optical and rheo-small angle neutron scattering (SANS) measurements, as well as simulation and theory. In particular, the shear-induced self-organization of "hydroclusters" (transient colloid concentration fluctuations) as predicted by Stokesian Dynamics simulations are measured and connected to the suspension rheology. The onset of shear thickening is demonstrated to be understood as a balance of convective, colloidal and hydrodynamic forces and their associated timescales. The limits of shear thickening behavior are also explored at extreme shear rates and stresses, where particle material properties come into play. Although many applications of concentrated suspensions are hindered by shear thickening behavior, novel materials have been developed around shear thickening fluids (STFs). Ballistic, stab and impact resistant flexible composite materials are synthesized from colloidal & nanoparticle shear thickening fluids for applications as protective materials. The rheological investigations and micromechanical modeling serve as a framework for the rational design of STF-based materials to meet specific performance requirements not easily achieved with more conventional materials, as will be discussed. (Phys. Today, Oct. 2009, p. 27-32)

Collective dynamics are widely observed during development of multicellular bodies and emerge as a result of communication among individual cells via signaling molecules. However, little is known experimentally of the fundamental features that describe how the highly nonlinear spatio-temporal dynamics at the single-cell level can give rise to coherent dynamics at the population level. Here we use a FRET-based sensor protein, combined with live-imaging, to monitor cytosolic levels of cAMP which serves as the messenger molecule in developing cells of social amoebae Dictyostelium discoideum to allow individual cells to aggregate to form fruiting bodies. Timelapse recordings of cell populations during the first 10 hours of development reveal the very onset of periodic spike-like signaling and sequential changes in the frequency at single cell level resolution. Collective cAMP oscillations in populations of cells under perfusion reveal a sharp phase transition between a decoupled state and collective behavior for a range of cell densities and dilution rates. These observations suggest that the intact population is able to drive itself to this transition spontaneously during development. Focusing on how single cell dynamics influence, and give rise to, the behavior of the aggregate, we develop a simple model of the single cell response to time-dependent pulses of the extracellular signaling molecule cAMP, characterized by a particular type of excitable system. We then use this model to study collective multicellular dynamics mediated by diffusion coupling. We first consider the mean-field case where we find an intriguing ``dynamical quorum sensing'' transition in which all cells simultaneously transition from quiescent to oscillating across the phase boundary. Then we include spatial dynamics and study pattern formation, both with and without the cells capable of chemotactic response to signal gradients. Finally, we highlight how modification of single cells can alter the collective dynamics.

Morphogenesis is the process that converts the DNA 'blueprint' of an organism into its physical shape, size and structure and is the ultimate of self-assembly. It is driven by intercellular interactions that control growth and patterning of tissues and bridge the gap between genes/molecules and macroscopic morphology. The talk will address the physical aspects of these morphogenetic interactions focusing, in the context of fly wing development, on i) the possible role of mechanical stress in the regulation of growth and on ii) the phenomenon of Planar Cell Polarity that is responsible for the orderly arrangement of epithelial cells. We shall see that morphogenesis naturally involves physics, although sometimes in unexpected ways.

Large populations may contain numerous simultaneously segregating polymorphisms subject to natural selection. In order to understand population genetics in this case, theoretical models must account for interactions between polymorphisms at different genetic loci and in different individuals. The effect of these interactions depends on the effective rate of recombination. The talk will use simple models of facultatively sexual populations (motivated by HIV intra-patient evolution) to provide quantitative insight into the effect of interaction and recombination on the dynamics of alleles. Specifically, we shall address i) the suppression of clonal interference (and the resulting acceleration of adaptation) by recombination, and ii) the Hill-Robertson effect, a.k.a. 'genetic draft', which accelerates fixation of neutral alleles and reduces the effectiveness of natural selection because of transient associations between polymorphic loci. We shall see that in the regime of relatively rare outcrossing, the effect of genetic draft is dominated by large fluctuations and is very different from the familiar, diffusive, genetic drift. In conclusion we shall discuss open questions and avenues for the application of these theoretical ideas, in particular in the context of HIV evolution.

There has been a great deal of confusion about the role of models in the financial crisis. In this talk I want to discuss the possible ways of describing and explaining the world. Scientific theories deal with the natural world on its own terms, and can achieve great truth and accuracy. Models in finance are not theories; they are closer to metaphors that try to describe the object of their attention by comparing it to something else they already understand via theories. Models are idealizations that always sweep dirt under the rug, and good models tell you what kind of dirt it is, and where it lies.

Many marine-terminating outlet glaciers in Greenland calve icebergs so rapidly that they produce persistent and densely-packed surface coverages of icebergs, sea ice, and brash ice in their proglacial fjords. The traditional glaciological viewpoint is that, unlike ice shelves, sea ice and icebergs are unable to exert significant backpressure on a glacier's terminus and have therefore no effect on a glacier's stability. However, visual and timelapse observations of these 'ice melanges' indicate that (1) they form semirigid, viscoelastic caps over the innermost 15-20 km of their fjords, (2) their motion is primarily accommodated by deformation and/or slip in narrow shear bands and is strongly influenced by glaciers pushing them from behind, and (3) they are able to inhibit iceberg calving during winter when sea ice helps to bind the iceberg clasts together. These observations suggest that ice melanges should instead be viewed as weak, granular ice shelves whose strength varies seasonally due to the growth and decay of sea ice, and are thus an important component of glacier-fjord systems. In this talk I will present results from the first field study of an ice melange and discuss some of the difficulties in instrumenting ice melanges and in incorporating their effects into large-scale ice sheet models.

Using a model system of 2D fluid-like membranes composed of homogeneous rod-like viruses, we investigate the structure and fluctuations of the membrane's edge. We provide experimental evidence that the chirality of the constituent rod-like molecules control the magnitude of the line tension associated with the edge of the membrane. For sufficiently chiral molecules, the line tension is reduced to low values causing spontaneous production of interfaces and leading to assembly of myriad chiral structures with unique properties. Using a combination of various microscopy techniques we elucidate the three dimensional structure of a few chosen assemblages at all relevant length scales. Finally, using optical trapping we create chiral assemblages with different architectures, thus enabling assembly of materials with complex topologies.

Neural systems adjust their gain to better encode the statistics of the environment. This occurs with the contributions of a range of processes that occur at several timescales. We show that the ability of a neural system to adjust its coding strategy to a stimulus' time-varying variance can be implemented at the level of single cortical neurons but only under certain conditions. We show that these conditions are attained by developing neurons in the course of their first week. The idea that neurons track time-varying statistics not only constrains the neural strategy, but also implies that the timescales of adaptation may be limited by the time required for inference. We show that, in the retina, optimal inference can reproduce the phenomenology of adaptation and makes new predictions for experiments.

While the phenomenon of drag reduction by polymer additives in turbulent fluid flows has been studied extensively, little is documented on the effect of polymer additives on heat transport in turbulent thermal convection. Turbulent thermal convection is often investigated experimentally in the setting of Rayleigh-Benard (RB) convection which consists of a container of fluid heated from below and cooled on top. In turbulent RB convection, there is an exact balance between the heat transport and the energy and thermal dissipation rates. Contributions to the dissipation rates come from the bulk of the flow as well as the boundary layers. In this talk, I shall discuss our study of the polymer effects on heat transport in both homogeneous turbulent thermal convection modeling the bulk of turbulent RB convection and boundary layer flows.

The extensive interactivity among genes that is now being revealed suggests that there is considerable flexibility in the genome's capacity for responding effectively to diverse conditions. In model gene networks affecting behavioral phenotypes in Drosophila, a high degree of flexibility has been observed and the interactions underlying the various states of the network have been analyzed.

I will summarize our recent progress in experiments and models of the locomotion of a sand-swimming lizard, the sandfish (Scincus scincus). We use high speed x-ray imaging to study how the 10 cm-long sandfish swims at 2 body-lengths/sec within sand, a granular material that displays solid and fluid-like behavior. Below the surface the lizard no longer uses limbs for propulsion but generates thrust to overcome drag by propagating an undulatory traveling wave down the body. To predict sandfish swimming speed in the granular 'frictional fluid', we develop an empirical resistive force model by measuring drag force on a small cylinder oriented at different angles relative to the displacement direction and summing these forces over the animal movement profile. The model correctly predicts the animal's wave efficiency (ratio of forward speed to wave speed) as approximately 0.5. The empirical model agrees with a more detailed numerical simulation: a multi-segment model of the sandfish coupled to a multi-particle Molecular Dynamics simulation of the granular medium. We use the principles discovered to construct a sand-swimming physical model (a robot) which, like in our empirical and multi-particle numerical model, swims fastest using the preferred sandfish wave pattern.

Growing evidence supports a critical role for metal-ligand interactions in some of the unique properties of soft biological polymeric materials. For example, the strength of the coordinate bonds in Fe- and V-catechol complexes combined with their capacity to reform after breaking has been proposed as a source of the self-healing in mussel adhesives and of the autonomous wound-healing in the outer body walls of sea-squirts, respectively. Inspired by the pH jump experienced by these marine bio-materials during secretion, we have developed a simple method to control metal-catechol inter-polymer crosslinking as well as tune visco-elastic properties of polymer networks. Tuning of metal-ligand interactions to control material properties could be a widespread strategy in Nature.

The collective dynamics of swimming bacteria, the formation of the Red Spot on Jupiter, and the presence of solitons in the Fermi-Pasta-Ulam problem are examples of large-scale coherence in many body systems. Such phenomena, being motions of relatively simple form, allow us to ask sharp questions about how nonlinearity organizes far-from-equilibrium dynamics. We study the impact of a densely packed granular jet. Previous experiments reveal that dense granular jet impact onto a target produces a thin ejecta sheet comprised of particles in collimated motion, reminiscent of the thin sheet formed when a water jet hits a fixed target. This unexpected liquid-like response in a high-speed impact echoes the collimated beam ejecta found at the relativistic heavy ion collider (RHIC), which has been described accurately by hydrodynamics. We use experiments and simulations to probe the velocity and stress fields inside the granular jet, and find that the collimated ejecta sheet coexists with a dead zone, a region of nearly stagnant particles. Removing friction at the target removes the dead zone without significantly affecting the ejecta dynamics. Finally, using a frictionless target, we find numerical results for the velocity and pressure fields within the granular jet agree quantitatively with predictions from an exact solution for 2D perfect-fluid impact. This correspondence demonstrates that the continuum limit controlling the coherent collective motion in dense granular impact is Euler flow. Therefore momentum conservation and incompressibility describe the dynamics observed in granular jet impact. (Collaborators Nicholas Guttenberg, Herve Turlier, Wendy Zhang, and Sidney Nagel)

Bird song, long since an inspiration for artists, writers and poets also poses challenges for scientists interested in dissecting the mechanisms underlying the neural, motor, learning and behavioral systems behind the beak and brain, as a way to recreate and synthesize it. In this talk I will present research done in collaboration with Prof L. Mahdevan (Harvard) and Prof S. Mandre (Brown) on quantitative visualization experiments with physical models and computational theories to understand the simplest aspects of these complex musical boxes, focusing on using the controllable elastohydrodynamic interactions to mimic aural gestures and simple songs. Progress on recent experiments on impulsive motion driven swimming fish-like 'robots' will also be presented.

How many times has this happened to you? You've just read Feynman's description of a wobbling plate (think a poorly thrown Frisbee), where he states that the rotation rate is twice the wobbling rate. You decide to check the result. You could set up a high-speed camera and film a wobbling Frisbee, you could review the mathematics of rigid-body rotations, or you could write a computer program to simulate a wobbling plate. All options sound too time intensive to you, so you don't check the result.

We are going to introduce you to VPython, a very easy-to-use Python-based programming package that allows you to create 3D animations of a wide variety of physical phenomena. A typical first year college student, with no prior computing experience, can create a simple simulation with less than an hour of instruction in the use of VPython. This talk will describe several computing projects for physics students, spanning a range of sophistication. In particular, we will show several projects, (covering billiards, random walks, fractals, and solitons as well as wobbling frisbees) that are intended for students in a bridge-to-research class such as the 'Chaos, Complexity, and Computing' (Physics 251) course taught at the University of Chicago.

Liquid Crystal (LC) films composed of chiral compounds are known to exhibit a unidirectional molecular rotation under transmembrane thermal, ionic or mass current. We have investigated the molecular precession in ultrathin free-standing chiral LC films driven by transmembrane gas flow, focusing on the question of what is the origin of the unidirectional molecular rotation. Our experimental result showed that there are two sources, one is macroscopic helix and the other is microscopic molecular propeller, the intersection of which was clearly observed. The transmembrane gas flow induces not only the molecular precession but also the unidirectional hydrodynamic flow in the films. Controlling the elasticity and boundary condition, we also observed the crossover between the two flows.

Soft matter systems derive their bulk mechanical properties from their underlying microscale structure and its response to thermal fluctuations. In this talk I will discuss how we are using our newly developed Confocal Rheoscope to simultaneously measure changes in the mechanical behavior and structural organization of materials such as shear thinning and thickening colloidal suspensions. Our studies have revealed the underlying entropic mechanisms, in-plane structural changes, and hydro-clusters that accompany transitions in the bulk material's flow response.

When two different materials are rubbed together, they will generally exchange electrical charge. This is called tribocharging. We think of this phenomena as occuring because it is energetically favorable for a few charge carriers to move from one material to the other. As appealing as this explanation is, it is a surprising and unexplained fact that identical materials can also systematically exchange charge, despite presenting no obvious energetic advantage. I will present results which show that in systems of identical, insulating grains, the asymmetry is somehow tied to the size of the grains, with large grains charging positively and small grains negatively. These results will be compared with an existing model for this phenomena, which we are currently trying to confirm or deny.

I will present resent results on the coarse graining of ODE models of crystal surface relaxation with Hala Al Ha jj Shehadeh and Robert V. Kohn. We consider a 1D monotone crystal surface and prove that the slope of a ?nite size crystal in this setting converges (in the long time limit) to a similarity solution. We also give an informal derivation of a fully non-linear fourth order PDE (large crystal) limit of the ODE's as well as analogues of our similarity results in the continuum. Rigorously establishing the convergence of the ODE system to the PDE remains a signi?cant challenge. If time permits I will also show preliminary results of a project with Jeremy Marzuola investigating certain scaling limits of a general family of Kinetic Monte Carlo models of crystal surface relaxation.

Young's classic analysis of the equilibrium of a three-phase contact line ignores the out-of-plane component of the liquid-vapor surface tension. While it has long been appreciated that this unresolved force must be balanced by elastic deformation of the solid substrate, a definitive analysis has remained elusive because conventional idealizations of the substrate involve a singular stress at the contact line. While a number of theories have been presented to cut off the divergence, none of them have provided reasonable agreement with experimental data. We measure surface and bulk deformation of a thin elastic film near a three-phase contact line using fluorescence confocal microscopy. The out-of-plane deformation is well fit by a linear elastic theory incorporating an out-of-plane restoring force due to the surface tension of the gel. This theory predicts that the deformation profile near the contact line is scale-free and independent of the substrate elastic modulus. Time permitting, I will briefly highlight our related work on another class of elastic singularities - the divergence of stress at the tip of a crack.

Ultracold dilute atomic gases can be considered as model systems to address some pending problem in Many-Body physics that occur in condensed matter systems, nuclear physics, and astrophysics. We have developed a general method to probe with high precision the thermodynamics of locally homogeneous ultracold Bose and Fermi gases [1,2,3]. This method allows stringent tests of recent many-body theories. For attractive spin 1/2 fermions with tunable interaction (6Li), we will show that the gas thermodynamic properties can continuously change from those of weakly interacting Cooper pairs described by Bardeen-Cooper-Schrieffer theory to those of strongly bound molecules undergoing Bose-Einstein condensation. First, we focus on the finite-temperature Equation of State (EoS) of the unpolarized unitary gas. Surprisingly, the low-temperature properties of the strongly interacting normal phase are well described by Fermi liquid theory [3] and we localize the superfluid phase transition. A detailed comparison with theories including Monte-Carlo calculations has revealed some surprises and the Lee-Huang-Yang beyond mean field corrections for low-density bosonic and fermionic superfluids are quantitatively measured for the first time. Despite orders of magnitude difference in density and temperature, our equation of state can be used to describe low density neutron matter such as the outer shell of neutron stars.

[1] S. Nascimbene, N. Navon, K. Jiang, F. Chevy, and C. Salomon, Nature 463, 1057 (2010) [2] N. Navon, S. Nascimbene, F. Chevy, and C. Salomon, Science 328, 729 (2010) [3] S. Nascimbene, N. Navon, S. Pilati, F. Chevy, S. Giorgini, A. Georges, and C. Salomon, Phys. Rev. Lett. 106, 215303 (2011)

Existing analyses of income taxation use very simple models of taxpayer behavior, often assuming that a taxpayer lives for only one unit of time and only receives labor income, and assumes that all taxpayers have the same preferences. I will outline a computational approach that uses tools from algebraic geometry, approximation methods, quadrature methods, and DFO methods.

The dynamics of a wide range of systems involve reactive events, aka activated processes, such as conformation changes of macromolecules, nucleation events during first-order phase transitions, chemical reactions, bistable behavior of genetic switches, or regime changes in climate. The occurrence of these events is related to the presence of dynamical bottlenecks of energetic and/or entropic origin which effectively partition the phase-space of the dynamical system into metastable basins. The system spends most of its time fluctuating within these long-lived metastable states and only rarely makes transitions between them. The reactive events often determine the long-time evolution of the system one is primarily interested in. In simple settings the Freidlin-Wentzell theory of large deviations provides a complete picture of how and when rare events occur. However, large deviation theory is valid in a parameter range where the random noise affecting the system is very small, which is often an inadequate assumption in complex systems. In addition, it becomes cumbersome to build numerical tools directly on Freidlin-Wentzell large deviation theory when the rare reactive events involves intermediates states, multiple pathways, etc. which is also the typical situation in high-dimensional systems. In this talk, I will explain why and describe a framework which allows to go beyond large deviation theory and can be used to identify the pathways and rate of rare reactive events in situations where the noise is not necessarily small, there are multiple pathways, etc. I will also describe numerical tools that can be built on this framework. Finally I will illustrate these tools on a selection of examples from molecular dynamics and material sciences.

My laboratory studies how the nervous system translates sensory information into behavior. Some of the rare examples where we know the complete path from sensory input to motor output are escape responses that allow animals to survive an encounter with a predator. My talk will focus on the escape response of the nematode C. elegans. The escape response serves as a paradigm neuronal control of behavior that requires: locomotion, sensory processing, decision making, generation and coordination of independent motor programs and navigation. I will discuss the molecular and cellular basis of this behavior and the ecological significance of the escape response in predator-prey interactions between C. elegans and predacious fungi that catch and devour nematodes.

At low temperatures, glasses and crystals behave in qualitatively different ways. In particular, glasses have a great many more low-energy excitations and have a different temperature scaling of the thermal conductivity. These low-temperature properties of glasses have traditionally been explained in terms of a distribution of dilute, two-level quantum states that are created by clusters of particles tunneling between two nearly degenerate ground states. Strong evidence for this model has come from the saturation effects and acoustic echoes observed in these excitations. In this talk I will show that, in contrast to conventional wisdom, the normal modes of model glasses can also produce acoustic echoes with similar features as found in the experiments. The quasi-localized, strongly anharmonic, normal modes of jammed systems can produce acoustic echoes due to the shift in the mode frequency with increasing amplitude. We see this both in jammed packings of spherical particles with finite-ranged, Hertzian repulsions, and in model glasses interacting with a Lennard-Jones potential. Our simulations suggest that an understanding of the low-temperature excitations in glasses does not require two-level tunneling states. A model based on jamming of particles is also able to produce a high density of low-energy excitations, a thermal conductivity similar to that found in glasses, and the echo phenomenon that had been thought to be unobtainable from normal-mode excitations.

In 1893 Lord Kelvin coined the term chirality, and stated what is to become the elementary paradigm of chirality: 'I call any geometrical figure, or any group of points, chiral, and say it has chirality, if its image in a plane mirror , ideally realized cannot be brought to coincide with itself'. While the notion of chirality has greatly advanced our understanding of the structures of molecules and crystals, it has been shown to be inconsistent with every pseudo-scalar quantification. In this talk I will present a tabletop demonstration of a chiral structure which is constructed through the achiral summation of identical elementary units which are symmetric under reflection. The seeming contradiction to the definition of chirality is reconciled by proposing an alternative definition, relying on the physicist interpretation of the right hand rule, as a relation between a rotation and a direction. Using this definition, well known pseudo tensors may serve as chiral measures, and the oriented nature of the chirality of molecules may be put to use.

One of the more interesting recent discoveries has been the ability to design nano/micromotors which catalytically harness the chemical energy in their environment to move autonomously. These 'bots' can be directed by information in the form of chemical and light gradients. Further, we have developed systems in which chemical secretions from the translating nano/micromotors initiate long-range, collective interactions among themselves. This behavior is reminiscent of quorum sensing organisms that swarm in response to a minimum threshold concentration of a signaling chemical. We will discuss recent experimental results, as well as approaches to the modeling of the complex emergent behavior of these particles.

Smectic liquid crystals combine the softness of one-dimensional order with the geometric elasticity of membranes. Typically, when they are observed near equilibrium, these materials harbor a variety of topological defects and rigid geometric structures. I will discuss a toolbox of constructions which elucidate these structures and allow us to build solutions with specific boundary conditions.

At the present time the most serious rate-limiting factor that prevents large-scale biological and palaeontological studies from being undertaken is a lack of capacity for delivering large numbers of accurate and consistent specimen identifications. Identifications by expert taxonomists based on qualitative inspection of morphologies are typically assumed to be 100% accurate. But recent blind test studies indicate that, in a variety of commonly encountered situations, consensus consistencies between identifiers can be as low as 43%. The obvious alternative to human expert-mediated species identifications is to automate some or all aspects of the identification process, at least for commonly encountered or particularly important species. A variety of computer vision-machine learning systems are available for this purpose. Recent experiments with these have yielded very encouraging results in small-scale trials (e.g., 2-30 group categories). The current challenge is to design, assemble, and test distributed networks of automated identification systems capable of accurately and consistently assigning unknown and unposed specimens to thousands of taxonomic categories. Scaling this technology up to the point where it can take over routine identifications is possible, but will require a sustained and well-organized collaboration between systematists and other specialists working in the areas of pattern recognition, machine learning, and artificial intelligence -- as well as technology engineers, software designers, and mathematicians.

The technique of 'coarse-graining' has been in existence for some time. As a result, numerous theoretical and computational models carrying this label have been proposed and published. Many different interpretations and increasingly strongly-held points of view on the methodology currently exist. In this talk a statistical mechanical perspective on coarse-graining will be presented that has connections to the concepts of renormalization as one way to frame this important and rapidly developing technique. A rigorous methodology will be presented for deriving coarse-grained (CG) models of complex liquids and other soft matter systems, such as peptides and proteins, from their underlying atomistic-scale interactions. The approach relies on a variational algorithm to renormalize the molecular forces into simpler effective forces at the lower resolution of the CG model. Recent developments to include three-body interactions at the CG level will be described that improve the accuracy of the resulting CG model. A valuable interpretive approach to decompose the coarse-grained interactions into their energetic and entropic components will also be presented. Some advantages and pitfalls of coarse-graining in general will be highlighted, as well as possible future directions.

We introduce a comprehensive theoretical framework for the fermionic superfluid dynamics, grounded on a local extension of the time-dependent density functional theory. With this approach, we describe the generation and the real-time evolution and interaction of quantized vortices, the large-amplitude collective modes, as well as the loss of superfluidity at high flow velocities. We demonstrate the formation of vortex rings and provide a microscopic description of the crossing and reconnection of quantized vortex lines in a fermion superfluid, which provide the mechanism for the emergence of quantum turbulence at very low temperatures. We observe that superfluidity often survives when these systems are stirred with velocities far exceeding the speed of sound.