In 1965-71, a group of people, myself included, formulated and perfected a new approach to physics problems, under the names of scaling, universality and renormalization. This work became the basis of a wide variety of theories ranging from particle physics and relativity, through condensed matter physics, and into economics and biology.

This work was of transcendental beauty and of considerable intellectual importance.

This left me with a personal problem. What next? Constructing the answer to that question would dominate the next 45 years of my professional life.

* The most important work came from Cyril Domb, Michael Fisher, Benjamin Widom, A. Pashinski, V. Pokrovskii, and Kenneth Wilson.

The lattice Boltzmann method (LBM) is a mesoscale approach, which can accommodate coarse-grained, molecular-level information into the macroscopic description of complex interfacial phenomena. This is achieved by introducing a phase field function into a single-phase lattice Boltzmann formulation to distinguish between phases (i.e. liquid/vapor, liquid/liquid), together with a phenomenological free energy functional of the solid-liquid-vapor system whose dissipative minimization constrains the temporal evolution of the phase field. LB equation is generally derived from the discrete Boltzmann equation by discretizing it on uniform rectangular mesh and usually comprises collision and streaming steps. While this greatly facilitates numerical procedure, it limits shapes of the computational domain that LBM can be applied to. This limitation could substantially increase computational effort for flows of boundary-layer type and in complex geometries with strong interactions between solid surface and contact line. To overcome geometric constraint of LBM and to improve its numerical stability at high Reynolds number, we have recently proposed high-order Galerkin/Discontinuous Galerkin Spectral/Finite Element LBM. In these computational frameworks, LB equation is regarded as a special space-time discretization of the discrete Boltzmann equation in the characteristic direction, and is solved by higher-order accurate schemes on unstructured mesh. In this presentation, a brief introduction to the temporal and spatial discretizations of the discrete Boltzmann equation will be given, with emphasis on the Galerkin/Discontinuous Galerkin approximations on unstructured mesh. Applications of the new LBM will be discussed in the simulations of single- and two-phase flows including flow past a cylinder, drop coalescence, and drop impact on thin liquid layer and flat/heterogeneous substrates.

We have recently found a way to describe the large-scale statistical dynamics of neocortical neural activity in terms of (a) the equilibria of the mean-field Wilson-Cowan equations, and (b) the fluctuations about such equilibria due to intrinsic noise, as modeled by a stochastic version of such equations. Major results of this formulation include a role for critical branching, and the demonstration that there exists a nonequilibrium phase transition in the statistical dynamics which is in the same universality class as directed percolation (DP). Here we show how the mean-field dynamics of interacting excitatory and inhibitory neural populations is organized around a Bogdanov-Takens bifurcation, and how this property is related to the DP phase transition in the statistical dynamics. The resulting theory can be used to explain the origins and properties of random bursts of synchronous activity (avalanches), population oscillations (quasi-cycles), synchronous oscillations (limit-cycles) and fluctuation-driven spatial patterns (quasi-patterns). If time permits we will also show how such a system of interacting neural populations can be made to self-organize to a state near the Bogdanov-Takens bifurcation, if the coupling constants (synaptic weights) are activity-dependent, and follow the rules of spike-time dependent synaptic plasticity (STDP).

In this talk, I will discuss recent progress in our understanding of a fundamental and non-linear coupling between in-plane order and out-of-plane geometry in twisted assemblies of filamentous molecules, key structural motifs in cells and living tissues. Not unlike the coupling of in-plane stresses and out-of-plane geometry in thin elastic sheets, we find that certain textures of filament tilt generate intrinsic stresses that frustrate the cross-sectional packing of bundles. Surprisingly this problem is formally akin to crystalline order on spherically-curved membranes, and sufficiently twisted textures of filament bundles favor the incorporation of one or more topological defects in the otherwise regular cross section of the bundle. Based on the non-linear continuum theory of filament arrays, we explore the complex spectrum of topological defects -- disclinations, dislocations and grain boundaries -- that thread through the ground-state packing of these materials and show that the structure of these highly-irregular packings is primarily governed by two geometric parameters relating to the degree of twist and the lateral size of bundles. Finally, I discuss a simple approach to exposing the hidden, non-Euclidean geometry of twisted bundles that underlies the frustration of in-plane packing in these materials.

The possible existence of a Bose-condensed supersolid state in solid 4He was first suggested over 40 years ago by Chester, Andreev and Lifshitz, and Leggett. The first experimental evidence for the supersolid has appeared only recently with the torsional oscillator experiments of Kim and Chan where they observed, at low temperature, a decrease in the period of an oscillator containing a solid 4He sample. They interpreted this decrease in period as superfluid-like decoupling of a fraction of the moment of inertia of the 4He sample from the motion of the torsional oscillator. This discovery created great excitement in the low temperature community and has been followed by a flurry of activity in many laboratories around the world. The Kim-Chan discovery was followed closely by the observation by Day and Beamish of an anomalous increase in the shear modulus of solid 4He in the same temperature range as the supersolid observation. It has developed that these two phenomena share many common features and appear to be closely related. The possibility exists that the period shifts seen in the torsional oscillator experiments may, at least in some cases, be a consequence of the shear modulus anomaly. At Cornell, we have constructed multiple-frequency torsional oscillators in an attempt to delineate the effects of the supersolid and shear modulus anomaly. This approach takes advantage of the expectation that the supersolid phenomenon, as in the case for superfluidity in liquid 4He, is relatively insensitive to frequency, while the effect of changes in the effect on the oscillator period will have pronounced frequency dependence. These measurements are currently in progress, however, we have been able to establish that in certain cases the shear anomaly is can produce period shift and dissipation signals identical in form to the supersolid signals reported by Kim and Chan. J.D.R would like to acknowledge the collaboration of Xiao Mi and Erich Mueller in the work and also the support of the NSF through Grants DMR-06586, PHY-0758104, and CCMR Grant DMR-0520404.

The prediction of crack path as it propagates into a brittle material is one of the main challenge in fracture mechanics. In the framework of Linear Elasticity Fracture Mechanics, the most important information governing the dynamics of crack growth can be found in the stress eld close to its edge. In the vicinity of the crack, the stress eld under a mode III shear tearing of a thin plate has a universal form but with a non-universal amplitude known as the Stress Intensity Factor. All the non-universal aspects of the stress distribution are collected in the Stress Intensity Factor which depends on everything, including the crack length, the boundary conditions and the history of the loads that drive the crack evolution. Although the equations of elasticity for thin plates are well known, there remains the question of selection of a path for a propagating crack. We invoke a generalization of the principle of local symmetry to provide a criterion for path selection and demonstrate the qualitative agreement of our results with the experimental ndings. We also ana- lyze the nature of the singularity at the crack tip with and without the nonlinear elastic contributions. Finally we present an exact analytic results for the stress intensity factor to the linear approximation for the crack developing in thin sheets.

Much like the bones in our bodies, the cytoskeleton consisting of filamentous proteins largely determines the mechanical response and stability of cells. These biopolymers form fiber networks, whose mechanical stability relies on the fibers' bending resistance, in contrast to rubbers that are governed by entropic stretching of polymer segments.Thus, the elastic and dynamic properties of such semi-flexible polymers are very different from conventional polymeric materials. We show that these networks exhibit both a low-connectivity rigidity threshold governed by fiber bending, as well as a high-connectivity threshold governed by fibre-stretching elasticity. We show that the latter exhibits rich zero-temperature critical behavior, including a crossover between various mechanical regimes along with diverging strain fluctuations and a concomitant diverging correlation length. Inspired by both intra- and extracellular networks, we describe recent theoretical modelling and experiments on simplified fiber networks in vitro. Among the more striking material properties of these networks is their nonlinear elasticity, with a strong stiffening response to stress. Unlike passive materials, however, living cells are kept far out of equilibrium by metabolic processes and energy-consuming molecular motors that generate forces to drive the machinery behind various cellular processes. We show how such internal force generation by motors can lead to dramatic mechanical effects, including a strong stiffening of cytoskeletal networks. Furthermore, stochastic motor activity can give rise to diffusive-like motion in elastic networks, as has been observed in living cells.

In stark contrast to nature, current manmade devices, with the exception of liquid crystals, make no use of nanoscale molecular motion. In order for molecules to be used as components in molecular machines, methods are required to couple individual molecules to external energy sources and to selectively excite motion in a given direction. Significant progress has been made in the construction of molecular motors powered by light and by chemical reactions, but electrically-driven motors have not been demonstrated yet, despite a number of theoretical proposals for such motors. Studying the rotation of molecules bound to surfaces offers the advantage that a single layer can be assembled, monitored and manipulated using the tools of surface science. Thioether molecules constitute a simple, robust system with which to study molecular rotation as a function of temperature, electron energy, applied fields, and proximity of neighboring molecules. A butyl methyl sulphide (BuSMe) molecule adsorbed on a copper surface can be operated as a single-molecule electric motor. Electrons from a scanning tunneling microscope are used to drive directional motion of the BuSMe molecule in a two terminal setup. Moreover, the temperature and electron flux can be adjusted to allow each rotational event to be monitored at the molecular-scale in real time. The direction and rate of the rotation are related to the chiralities of the molecule and the tip of the microscope (which serves as the electrode), which illustrates the importance of the symmetry of the metal contacts in atomic-scale electrical devices.

We examine solidification in thin liquid films produced by annealing amorphous films in a solvent vapor. Micrographs captured during annealing reveal the nucleation and growth of single-crystal needles. The needle lengths scale like power laws in time where the growth exponent depends on the thickness of the deposited film. The evolution of the thin film is modeled by a lubrication equation, and an advection-diffusion equation captures the transport of material and solvent within the film. We define a dimensionless transport parameter which describes the relative effects of diffusion and coarsening-driven advection. For large values of this parameter, needle growth matches the theory of 1D, diffusion-driven solidification. For low values, the collapse of droplets -- i.e. coarsening -- drives flow and regulates the growth of needles. Within this regime, we identify and analyze two asymptotic limits: needles that are small compared to the typical drop size, and those that are large.

Neurons explanted from the brain will grow on the bottom of a dish and form a highly connected, electrically active neural network. We show that its computational abilities are determined by collective effects in a new kind of percolation system, and are limited due to random connectivity. Geometrical guidance, along with redundancy and multiplexing, reproduce some minimal yet reliable computation functions of the network.

The behavior of a thin elastic sheet can be characterized by its 'bendability', a number that compares bending and stretching forces applied to the sheet. Highly bendability sheets are so thin that bending energies are essentially negligible. Because of this, highly bendable sheets wrinkle easily when subject to confinement. Traditionally, such wrinkles have been described by a 'post-buckling analysis' that describes the wrinkled state as a perturbation of the flat, un-buckled state. We argue that this is inappropriate for highly bendable sheets, since wrinkles are able to reduce the compressive stress essentially to zero. Instead, a 'far-from-threshold' analysis, in which wrinkles are treated as a singular perturbarion of a collapsed compressive stress state, must be used. A simple planar problem is used to illustrate this method, which is then used to analyze the behavior of thin sheets on liquid drops. Experiments demonstrate the need for this far-from-threshold analysis, but they reveal additional unexpected behavior.

Despite being composed of molecular components subject to intense thermal fluctuations, living cells routinely display strikingly precise and coherent behavior. A recently discovered example of this phenomenon is a ~24-hour oscillator found in the photosynthetic cyanobacterium Synechococcus elongatus. In a realistic environment, this oscillator is phase-locked to the daily rhythms of light and dark experienced by the organism, but precise oscillations will continue even if the organism is deprived of rhythmic cues. Thus, it is similar in function to the circadian clocks found in animals and plants, familiar to anyone who has become jet-lagged following a cross-country flight. Surprisingly, three purified protein components from this organism, KaiA, KaiB and KaiC, can be mixed in a test tube with ATP to reconstitute stable biochemical oscillations outside of the cell. Though the phase of this oscillation can be quite responsive to the environment, the period remains close to 24 hours over a broad physiological range of temperatures, protein concentrations and nucleotide conditions. I will describe a combination of biochemical experimental work and dynamical systems analysis in our attempt to understand both the emergence of robust oscillations and phase shifting in this simple system.

When Soviet nuclear scientists and engineers developed the RBMK (the 'Chernobyl-type' reactor), they were convinced that this design surpassed its rivals in every regard: it was easy to assemble, economical, and so safe it didn't need a containment structure. An experienced pool of operators was ready, having been trained on the RBMK's military and dual-use cousins. The first RBMK was built less than 50 miles from Leningrad, and by 1986 fourteen more were up and running, delivering a total of 15.5 GWe. After the Chernobyl disaster, critics portrayed the RBMK as technically flawed, incompetently operated, and part of a corrupt, mismanaged industry. Very similar charges were mounted in the aftermath of the Fukushima disaster: concerns about the Mark I containment allegedly date back to the early 1970s; Tepco, the utility, had attempted to cover up safety violations in the past; and the Japanese nuclear industry in general maintained too cozy a relationship with the regulatory agency. Poised to learn the lessons of Fukushima, the U.S. government has ordered a safety review of American reactors and simultaneously granted a license to a new, inherently safe reactor design; several more designs are under review. This talk will discuss what we would gain from taking the long view instead of focusing only on the immediate aftermath of a serious accident. I will argue that safety is more than technical reliability, and that it needs to be understood in the context of complex, messy historical, organizational, and cultural dimensions that defy standardization. Finally, the talk will raise a few related questions about the role of small modular reactors for our future energy policy.

Glassy systems are ubiquitous in nature, from window glasses, through the anomalous magnetic properties of spin-glasses, to memory effects observed in electronic systems. Among their key properties are slow relaxations to equilibrium without a typical timescale and aging, the dependence of relaxation on the system's age. Understanding these phenomena is a long-standing problem in physics. In this talk I will show that the particular example of electron glasses is a useful case study to understand the generic mechanisms involved, leading to aging. I will describe our approach to the problem, and show that it generally leads to a particular form of aging, which we found to agree well with data on electron glasses, as well as various other systems such as disordered semiconductors and structural glasses. I will also show results on the expected deviations from the universal form, and what we think can be learnt from them.

In this talk I will describe experiments to study the properties of electrons immersed in liquid helium. By using an ultrasonic technique it has been possible to make movies showing the motion of individual electrons. I will describe the details of the experiments and show the results that have been obtained.

Bacterial suspensions, extracts of cytoskeletal filaments and motor proteins, and cell colonies are examples of assemblies of interacting self-driven units that form a new type of active soft matter with intriguing collective behavior. In this talk I will discuss the theoretical modeling of active systems. Specific examples will include bacterial swarming and the collective migration of confluent layers of epithelial cells that have been shown to exhibit glassy dynamics at high density.

This is an experimental study on the conditions in which an airstream can displace liquid drops deposited on a solid surface. We vary the size of the drops, the wettability conditions and the viscosity of the liquid. The drift speed of the droplets is interpreted by balancing the viscous dissipation within the liquid and the work of the aerodynamic force. Larger drops, flattened by gravity, have drift speeds different from small droplets which remain nearly spherical.

When small solid particles encounter liquid interfaces, they can assemble into a variety of structures, including crystals, clusters, and gels. But the dynamics of assembly and the interactions that drive it are still not well-understood. We use digital holographic microscopy and confocal microscopy to directly observe colloidal particles in the early stages of self-assembly. These experiments have revealed unexpected dynamics in seemingly simple phenomena, such as the binding of a single colloidal particle to an interface. We find that a particle takes a surprisingly long time -- weeks or even months -- to relax to equilibrium. This behavior can be understood in terms of a dynamic wetting mechanism involving thermally-activated hopping of the contact line over surface defects. The results call into question the validity of models of colloidal interactions that assume the particles have reached equilibrium with the interface. They also suggest new ways to control these interactions and the resulting self-assembled structures.

This talk reviews the fundamental physical limits to computation and shows how they can be approached. Quantum mechanics governs the speed at which elementary logical operations can be performed. Statistical mechanics governs limits to memory space and to dissipation during computation. Special relativity governs speed of communication, and general relativity and quantum mechanics combine to govern the amount of information processing that can be performed in a volume of space and time. Implications for computer design are discussed.

Understanding and modeling soot particle dynamics in combustion systems is a key issue in the development of low emission engines. In engines, soot particles are formed as a result of complex hydrocarbon chemistry and are subject to a turbulent flow field which controls ultimately the yield of soot particles. In this work, we will detail the strategies used to model the various chemical and physical processes encountered both in laminar and turbulent flames. More precisely, we will consider the impact of the chemistry on the inception of the first soot particles, the geometrical and statistical representation of fractal aggregates, the oxidation and fragmentation of particles under lean conditions, and finally the turbulent transport of soot in complex unsteady flows. For each of these cases, we will compare our results with experimental measurements and discuss the differences. Finally, we will discuss results of a Large Eddy Simulation of a sooting turbulent jet diffusion flame with detailed chemical and soot models. This last simulation highlights the challenges in modeling soot evolution in turbulent flames due to the nonlinear interactions between the particles and the gas-phase turbulent combustion processes.

We report the first experimental measurements of nonlinear rheological material properties of hagfish gel, a volume-expanding self-defense material composed of a hydrated biopolymer/biofiber gel network. To explain the observed nonlinear viscoelastic behavior, we develop a microstructural constitutive model that has also proven useful for other biopolymer physical gels with non-covalent crosslinks. The linear elastic modulus of the network is observed to be G' ~ 2 Pa for timescales of 0.1s to 10s, making it one of the softest elastic biomaterials known. Nonlinear rheology is examined via simple shear deformation, and we observe a secant elastic modulus which strain-softens at large input strain while the local tangent elastic modulus strain-stiffens simultaneously. This juxtaposition of simultaneous softening and stiffening suggests a general network structure composed of nonlinear elastic strain-stiffening elements, here modeled as Finite Extensible Nonlinear Elastic (FENE) springs, in which network connections are destroyed as elements are stretched. We simulate the network model in oscillatory shear and creep, including instrument effects which cause inertio-elastic creep ringing. The network model captures the simultaneous softening of the secant modulus and stiffening of tangent modulus as the model enters the nonlinear viscoelastic regime.

Synthesizing multiple global measurements of cellular characteristics into a coherent whole remains an essential aim of the post-genomic era. Yet most syntheses fail to contend with two major issues: inescapable and varying measurement variability between groups, and massive amounts of missing data. Such failures have consequences. For example, it is widely accepted that cells use transcriptional regulation to shape steady-state protein levels, but the modest correlations between mRNA and protein measurements (about 0.6) have been repeatedly interpreted as prima facie evidence for alternate modes of regulation. An unappreciated alternative is that the correlation is actually very high, but the data are noisy. As Spearman noted a century ago, measurement error ensures that the correlation between two unbiased measurements underestimates the true correlation between the measured variables---and, crucially, this attenuation may be corrected. Applying a novel factor-analytical framework to decades's worth of measurements of mRNA levels protein levels during exponential growth of budding yeast in rich medium, we show that the correlation between mRNA level and protein abundance is greater than 0.9, suggesting that previous analyses have argued a larger role for other forms of regulation than the data demand. The general problem addressed here, while underappreciated in biology, is endemic to scientific inquiry and well-known in other fields.

We perform molecular dynamics (MD) simulations of spherical grains subjected to cyclic, quasi-static shear in a 3D parallelepiped shear cell. Using a standard routine for MD simulations of frictional grains, we simulate thousands of shear cycles, measuring grain displacements, the local packing density and changes in the contact network. We find that cyclic shear leads to dynamic self-organization into several phases with different spatial and temporal order. We present a phase diagram in strain - friction space which shows chaotic dispersion, crystal formation, vortex patterns and most unusually a disordered phase in which each particle precisely retraces its unique path. Particles remain in these periodic trajectories despite the fact that the contact network reveals a sizable fraction of disconnects in this limit cycle.

In the natural world, temporal correlations between events exist on many timescales, allowing organisms to anticipate the future state of their environments. A neural system that uses predictions to guide behavior must encode the future values of sensory inputs. This suggests a new approach to neural encoding. While most studies have, historically, sought to characterize what stimuli in the past gave rise to a response, we ask instead what stimuli those responses predict. We have found such 'predictive information' in the population responses of retinal ganglion cells (RGCs) in the larval salamander. To quantify predictive information, we ask how much RGC responses at some time 'now' (Rp) tell us about the future state of the stimulus (Sf). This information, I(Rp,Sf), is bounded by correlations in the stimulus itself, I(Sp,Sf). We show that nearly every cell in the retina participates in an N-cell group that saturates this bound. Coding for prediction may be a useful strategy for neural systems to adopt, making transfer of sensory information more efficient by compressing signals along dimensions relevant for behavior.

Most models of language dynamics seek to explain how processes of replication and selection can give rise to shared lexical and grammatical systems within human communities. They typically assume that communities are homogeneous, in the sense that everyone brings to language acquisition and processing the same cognitive abilities and biases. In general, they predict that linguistic systems should be more uniform and more stable than they really are.

In this talk, I will summarize some of the key empirical challenges to these first-generation language dynamics models. Then, I will show that a more realistic and insightful picture is obtained by assuming that linguistic communities are heterogeneous and non-ergodic. The talk will bring together in-depth statistical analyses of discourse in on-line communities, and numerical simulations of linguistic innovation in social networks. I will show that individual differences are pervasive, and that incorporating them in simulations helps to explain how new words and grammatical constructions can often come to be widely adopted.

When a dense granular jet impacts upon a target, the outflow is highly collimated even in the absence of attractive interactions. At long distances from the target, however, this collimated flow breaks up in the form of long-wavelength ripples. These ripples are a memory of transverse fluctuations induced by buckling above the target, amplified by ballistic motion. The response of the system to upstream fluctuations is examined by perturbing the flow with an external sinusoidal forcing. Beyond the target there are few interactions, and so the fluctuations are either retained or destroyed in the diverging flow right above the target. As such, the ripple spectrum and more generally the transfer function tell us about the behavior of this dense granular flow in the collision region.

Dispersion and migration of bacteria under flow in tortuous and confined structures such as porous or fractured materials, is related to a large spectrum of practical interests, but is still poorly understood. Here, after a brief introduction to the fields of active matter and microfluidics, we address the question of transport and dispersion of an E-coli suspension flowing though a micro-fluidic channel with a funnel-like constriction in its center. We show a counter-intuitive symmetry breaking of the bacteria concentration, which increases significantly past the funnel. This concentration enhancement persists over large distances from the funnel and disappears at large flow rate values. We map our results onto a one dimensional convection/diffusion equation predicting quantitatively the experimental results, without free parameters, when a conservative non-local source term is introduced. Our model experiment opens the possibility to control the concentration of bacteria suspensions in micro-fluidic channels by simply tuning the flow intensity or direction.

Traditionally, order in solids referred to periodic crystalline order. Since 1984, quasicrystals have been defined and identified, expanding the class of ordered systems. This leads naturally to the question of whether there are other types of order, neither periodic nor quasiperiodic, and if so, are such arrangements physically possible. Some recent ideas on this subject will be presented.

Quantum phase transitions (QPT) are fundamentally different from their classical counterparts, mixing statics and dynamics. I will describe our experimental approaches to two such QPTs. In the first part, I will show that the precise measurement of lattice distortions can reveal information about magnetic phase transitions in a material with strong spin-lattice coupling. Combining synchrotron x-ray and diamond anvl cell techniques, we consider a set of interacting dimers on a square lattice to uncover the magnetic phase diagram of the Shastry-Sutherland model in SrCu2(BO3)2. For the second part, I will consider quantum criticality at a Mott-Hubbard metal-insulator transition in NiS2. We have used x-ray diffraction to track magnetism and lattice symmetry to show that neither plays a driving role at the phase transition, and that the transition is solely driven by electronic correlations. Finally, we explore the critical region of the phase transition in search for scaling laws using high-pressure transport measurements.

Fluid vortex loops (e.g. smoke rings) linked together or tied into knots are the basis of a topological interpretation of fluid mechanics. In perfect fluids, the linking of vortex lines is preserved indefinitely and associated with a conserved quantity known as helicity. The situation is considerably more complicated in real fluids - even superfluids - because the vortex topology can change through local reconnections whose dynamics are not well understood. Previous attempts to study these phenomena in experiments have failed because no controlled method existed for making vortex knots in the laboratory. In this talk, I will describe a method we recently developed for making simple knotted vortices using 3D-printed hydrofoils. We measure the subsequent evolution of the vortex structures (a trefoil knot and pair of linked rings) using high-speed laser scanning tomography. We observe that they spontaneously untie/unlink themselves through a series of local reconnections, which we resolve in detail.

Numerous studies in recent years have suggested that climate sensitivity - the response of the climate system to imposed radiative forcing, e.g. by addition of CO2 - cannot be determined simply by examining short-term climate evolution. Climate models are broadly consistent in suggesting that extrapolating initial climate behavior would lead to underpredicting climate sensitivity and eventual equilibrium temperature after CO2 stabilization. Initial rates of ocean heat uptake would imply an equilbrium temperature some 75% of its final value: ocean heat uptake is nonlinear with global mean temperatures on long timescales. The computational demands of climate models has meant though that evolution is generally inferred indirectly by comparing relatively short (century-scale) climate runs with steady-state calculations. Rather than extrapolating from short-term behavior, we leverage computational resources at U. Chicago/Argonne to generate multi-millenial model runs that allow us to directly identify causes of this nonlinear behavior. We drive the NCAR CCSM3 model at relatively low spatial resolution (3.75 degrees) with increasing CO2 and observe transient climate repsonses for > 5000 years after stabilization. Results show that the conventional representation of long-term climate evolution as a changing ocean heat uptake efficacy does not capture the underlying physical processes, and the evolution is better represented as a nonlinear response in cloud forcing that sets in only after several hundred years. We show further that these temporal changes do not primarily reflect nonlinearity in cloud feedbacks but instead are largely an artifact of inhomogeneous warming. Because local cloud feedbacks differ in magnitude and sign across the Earth's surface, differential rates of warming, and especially the long delay in warming of the Southern Ocean, produce apparent nonlinear response even in the case of linear physics. Warming rates themselves are controlled by ocean turnover times, as is demonstrated by the tight relationship between nonlinear behavior in radiative forcing and in transient precipitation response, though these signals derive from different physical mechanisms in different locations. Our results are robust across forcing amounts and forcing agents. Though confirmation in other models would be important, these conclusions should be qualitatively robust across models as well. The general principle of local control of cloud forcing combined with latitudinally differential warming should produce similar behavior even if specific cloud responses differ between models.

Henry King: A Break with tradition: from Stores to Flows

Synopsis: From store logic to flow sense: a break in how we think about the world. For the last 10,000 years or so we have made stores of animals, plants, ideas, money, people, water, and other potential resources in order to maximize their usefulness to us. Now be the time for a different approach.

Bio: Henry King is an independent innovation consultant, using the methods and tools of innovation and IT to help organizations and regions achieve their transformation goals. His client list includes organizations of all types and sizes in USA, Europe, the Middle East, SE Asia and the former Soviet Union. He is currently helping a commercial/non-profit/educational consortium design a new model for health and wellbeing in rural Appalachia. He is also helping design new school models in the USA and in the Middle East.Henry is a part time faculty member and design council member of the School of the Art Institute of Chicago, where he teaches in the Department of Architecture, Interior Architecture and Designed Objects, and he engages with students and multi-disciplinary faculty in the areas of innovation, design and creativity. Henry studied Classics at Oxford University. He has written on innovation themes in Businessweek and Fast Co. Design.

Heinrich Jaeger: Breaking Granular Fluids

What if the molecules in a liquid were 100,000 times larger than normal? This unfamiliar world of ultra-low surface tension can be realized in fluids comprised of seemingly simple granular material, for example in jets of fine dry sand or in freely flowing powder streams. I will discusses recent experiments where we track with high-speed video and computer simulations how granular fluids evolve and eventually break apart into droplets.

Wendy Zhang: What is the sound of a glacier breaking?

During the summer, glaciers in Greenland flowing into the ocean shorten in length by calving icebergs from their seaward edges. Icebergs that are long and narrow slabs capsize as they calve. Each capsize releases an enormous amount of energy into the surrounding environment. It also gives rise to long-period seismic waves detectable over the entire earth. At present we do not understand how the energy released by an iceberg capsizing is subsequently partitioned among processes such as mixing of the stratified ocean water, compression of the ice melange, or generation of small-scale tsunami waves; nor do we know to what degree the seismic signals can be decoded to give specific physical information about the condition of the glacier. I will describe ongoing efforts to address these questions using table-top experiments and models of idealized capsizes.

Alan Rhodes: Breaking & Barriers: Between the Virtual and the Real

Synopsis: This brief talk will critically inspect the subversion, confusion and breakage of barriers between the 'virtual' and the 'real' in contemporary media art and their roots in video art performance of the 1970s. The talk, itself, will be in the form of a (new) mediated performance.

Bio: Geoffrey Alan Rhodes is a media artist, filmmaker, and writer. His works seek out new connections and experiences in the borders between the real and the virtual, the cinematic and the actual, fine art and popular experience. Rhodes' short films have screened and been installed at the International Film Festivals of Moscow, Mumbai, Sarajevo, Friesland, Goteborg, Cottbus, Split, Syracuse, and more. His installation works use multiple screens, projections, and live augmented video in explorations of auto-performance and the emergence of contemporary phantasmagoria. His works have been part of major exhibitions at Mediations Poznan Biennale Poland, the European Media Arts Festival, Microwave International Hong Kong, the International Society of Electronic Arts, and the Abandon Normal Devices Festival (UK). Rhodes is currently a member of the faculty of Visual Communication Design at the School of the Art Institute of Chicago.

Dan Price: Caesura: studio experiments in sculptural photography

Synopsis: A sculptor reflects on past experiments and presents a studio project in process, offering a brief discourse on the nature of photography and the possibilities wrought by its playful infidelity to time and space.

Bio: Dan Price lives and works in Chicago, IL where he is Assistant Professor of Sculpture at the School of the Art Institute of Chicago. He holds a B.A. in Fine Art from the Colorado College and a M.F.A. in Sculpture with honors from the Rhode Island School of Design.

Price has exhibited his videos and sculpture at the Kennedy Museum in Athens, Ohio, Triple Candie Gallery, New York; White Columns Gallery, New York; Angstrom Gallery in Los Angeles and at the Rhode Island School of Design Art Museum in Providence.

Price has worked as artist-in-residence at Art Omi in New York, Can Serrat in Spain, Elsewhere Elsewhere in Greensboro, NC and the Banff Centre in Canada. He has taught Art and English in a Xhosa high school in South Africa, and has worked for several design/build firms including nodesign in New Orleans and Glass Project in Jamestown, Rhode Island.

Dr. Sidney Nagel: Topological Transitions and Singularities in Fluids: The Life and Death of a Drop

Synopsis: The exhilarating spray from waves crashing into the shore, the distressing sound of a faucet leaking in the night, and the indispensable role of bubbles dissolving gas into the oceans are but a few examples of the ubiquitous presence and profound importance of drop formation and splashing in our lives. They are also examples of a liquid changing its topology: the fluid forms a neck that becomes vanishingly thin at the point of breakup. Singularities of this sort often organize the overall dynamical evolution of nonlinear systems. I will first discuss the role of singularities in the breakup of drops. I will then discuss the fate of the drop when it falls and eventually splashes against a solid surface.

Many complex phenomena are so familiar that we hardly realize that they defy our normal intuition; we forget to ask whether or not they are understood. Examples include the anomalous flow of granular material, the long messy tendrils left by honey spooned from one dish to another, the pesky rings deposited by spilled coffee on a table after the liquid evaporates or the common splash of a drop of liquid onto a countertop. Aside from being uncommonly beautiful, many of these phenomena involve non-linear behavior where the system is far from equilibrium. Most of the world we know is beyond description by equilibrium theories, and understanding far-from-equilibrium behavior is one of the great challenges of modern physics -- these are phenomena that can lead the inquisitive into new realms of physics. Problems such as these fuel much of my research effort.

Electrons nearing the surface of liquid helium, can become weakly bound ot the interface, floating several nanometers above the surface. Levitating essentially in vacuum, electrons on helium have the highest known electron mobility and extremely long predicted spin coherence. Further, it has recently become experimentally possible to manipulate thousands of floating electrons in parallel using CCD's much like those used in digital cameras. Yet thus far the coherence of individual electrons has eluded measurement. I will present a new cavity quantum electrodynamics inspired technique for both detecting the quantum state of the electron's spin and motion as well performing gates between electrons. Finally, I will describe present preliminary results on electron trapping and detection.

When an unstable iceberg tips over, a large amount of gravitational potential energy is released into the surrounding ocean. For this reason iceberg capsize has been hypothesized to play a role in the rapid disintegration of Antarctic ice shelves and the generation of glacial earthquakes which can be detected by the Global Seismic Network. However, direct observation of these events is difficult due to their remote locations and unpredictable nature. We use a combination of laboratory wave-tank experiments and numerical modeling to investigate hydrodynamic forces generated during iceberg capsize. In particular, I will show how the hydrodynamic coupling between adjacent icebergs can force them to capsize in a cooperative manner and accelerate their subsequent expansion across the ocean's surface. In addition, experiments of iceberg capsize near a rigid wall, such as a glacier terminus, show that hydrodynamics can significantly increase the magnitude and duration of the contact force with the terminus, and that the earthquake magnitude, expressed as a twice-integrated force history, is not simply proportional to iceberg size.

Sand ripples generated by oscillatory flow beneath water waves, a familiar feature of beaches, have been studied for many years because they control bed roughness, record paleoenvironmental conditions, influence reservoir properties, and form visually arresting patterns. Yet remarkably little is known about how the crests and troughs that define these patterns adjust as waves and tides shift. We have conducted laboratory wave tank experiments and numerical simulations to discover the meaning of defects in wave ripples - irregularities that disrupt an otherwise uniform array of crests and troughs - that have been observed in modern environments and in ancient rocks. Time-lapse images of the laboratory experiments show how defects accommodate changes in the ripple wavelength as water waves vary. The numerical simulations explore the long-term evolution of the defects and their relationship to flow structures. We find that some defects are unique signatures of changes in wave height or water depth, and provide a window into ancient coastal environments, whereas others are similar to defects observed in many patterns composed of approximately parallel features, such as animal stripes and optical wave fronts.

Nonlinear vibrations are attracting interest in many areas, from nanomechanics to circuit and cavity QED to Josephson junctions. They also allow one to address a fairly general problem of quantum fluctuations in systems away from thermal equilibrium. We will show that these fluctuations display unusual features, including the mechanism of switching between coexisting stable states of forced vibrations that has no analog in equilibrium systems. We call it quantum activation. It limits the precision of quantum measurements with oscillators. The scaling behavior of the switching rates will be outlined and a comparison with experiment will be made. Fragility of the rates of rare events like interstate switching will be also discussed.

Hawking's prediction that black holes radiate thermal radiation due to some sort of quantum instability was one of the biggest surprizes in physics of the last third of the 20th century. That quantum instability occurs in many other systems well allowing one to study its properties experimentally and theoretically. I will describe the process and an experiment which was carried out at UBC to measure the thermal spectrum of that radiation from a horizon in water flow along a flume.

Many species of songbirds do not sing instinctively but learn their songs by a process of auditory-guided vocal learning that (for zebra finches) starts with a kind of babbling that converges over several months and through tens of thousands of iterations to a highly precise adult song. How the neural circuitry of the songbird brain learns, generates, and recognizes temporal sequences related to song are important questions for neurobiologists and also interest an increasing number of physicists with backgrounds in statistical physics, nonlinear dynamics, biophysics, and device physics. I will discuss some of the interesting theoretical issues posed by recent experiments on songbirds, especially in regard to extremely sparse neuronal firing associated with song production. I will then discuss a theoretical model known as a synfire chain that my group and others have invoked to explain some features of the experimental data, and discuss some steps that will be needed to test this model experimentally.

In 1997, Nancy Kanwisher and colleagues published a paper describing an area in the human brain that showed strongly increased blood flow in functional magnetic resonance imaging (fMRI) experiments when people viewed pictures of faces compared to pictures of objects (1). This seemed to offer an ideal potential preparation for tackling the problem of how the brain extracts global visual form: a small piece of brain specialized to encode a single visual form. Thus, 12 years ago, Winrich Freiwald and I began a journey into exploring the neural basis of face processing. We decided to look for a face-selective area in macaque monkeys, reasoning that it would not be unreasonable to find such a region in monkeys, since face recognition is also integral to macaques.and most importantly, if we did find such a region, then we could target an electrode to the region (something not possible in humans) and directly record from individual neurons to ask how they are encoding faces. In my talk, I will discuss the anatomical and functional organization of the macaque face processing system.

-- Special Talk at 2:30 PM in Ryerson 251 --

Christopher Ortner, The University of Warwick

Optimising Multiscale Defect Simulations

The computation of geometry, energy (and other quantities of interest) for crystalline defects has been an active area of research for computational physics for at least 60 years. More recently, multi-scale approaches have been employed, to accelerate these computations, or to obtain higher accuracy. In this talk, I will focus on atomistic-to-continuum (quasicontinuum) methods for lattice defects. I will review how the framework of numerical analysis leads to error estimates (accuracy) in terms of the various approximation parameters such as domain size, atomistic region size, finite element mesh, or interface treatment. I will then discuss how these estimates can be recast as error estimates in terms of computational cost. Finally, this can be used to optimise the various approximation parameters. (Joint work with Helen Li, Mitch Luskin, Alex Shapeev and Brian Van Koten)

Although the concept of quasicrystals was introduced thirty years ago, there remain many basic open questions about how it forms and why it forms. This talk will note some of the theoretical issues and how it motivated a search for a natural quasicrystal, that, remarkably, has ultimately led to new questions about the origin of the solar system.