In this talk I will discuss how physics concepts can be useful for understanding issues arising in the field of computational complexity, the study of the amount of computational resources needed to solve different problems. In particular, I will present a renormalization group construction similar to those used in studies of phase transitions that may be useful in distinguishing computational problems that can and cannot be solved efficiently.

Since the nineteenth century, conformal mapping has been used to solve Laplace's equation by exploiting the connection between harmonic and analytic functions. In this talk, we note that another special property of Laplace's equation -- its conformal invariance -- is not unique, but rather is shared by certain systems of nonlinear equations, whose solutions have nothing to do with analytic functions. This simple observation leads to some unexpected applications of conformal mapping in physics. For example, it generates a multitude of exact solutions to the Navier-Stokes equations of fluid mechanics and the Nernst-Planck equations of electrochemical transport. It also allows conformal-map dynamics for continuous and stochastic Laplacian growth (in models of viscous fingering and diffusion-limited aggregation, respectively) to be extended to a variety non-Laplacian growth phenomena on flat and curved surfaces. This formulation enables computer simulations of otherwise intractable problems, such as advection-diffusion-limited aggregation of up to 100,000 particles in a fluid flow (evolving with the aggregate). It also provides analytical insight into the average shape of fractal clusters grown by multiple, competing transport processes.

This talk will review the general theory of nonlinear elasticity including definitions of deformations, strains, and stress tensor and how symmetries are implemented in elastic energies. It will then consider two examples in which nonlinear rather than the more familiar linearized elasticity is essential: nonlinear response of biopolymer networks and liquid crystalline elastomers. The latter systems exhibit transitions from microscopically isotropic rubber phases to ones exhibiting varying degrees of liqiud crystalline order. In their idealized form, these transitions break continuous symmetries with associated Goldstone modes whose manifestation is the vanishing of certain shear elastic constants and soft non-linear stress-strain relations.

We consider the gasless solid fuel combustion model of the Self-Propagating High-Temperature Synthesis process in which combustion waves are employed to synthesize desired materials. Specifically, we consider the combustion of a solid sample in which combustion occurs on the surface of a cylinder of radius R. We consider solution behavior as R is increased. If R is sufficiently small, planar pulsating waves are observed. As R is increased transitions to more complex, nonplanar waves occur. The study of different wave types is important since the mode of propagation determines the structure of the product. We describe a variety of different waves, including (i) spin waves, (ii) counterpropagating (CP) waves of various types, (iii) alternating spin CP waves (ASCP), (iv) modulated spin waves, (v) bound states of asymmetric spin waves, (vi) modulated asymmetric spin waves, (vii) asymmetric ASCP waves, and others.

While materials are most commonly thought of as solids, liquids, or gasses, a tremendous variety of everyday materials (biological materials, consumer care products, foods, etc.) elude such easy classification. Rather, they fall somewhere in between -- e.g. solids on short time scales and fluids on long time scales. Over many decades, techniques in rheology have been developed to study how such materials deform and flow. Conventional rheology is 'macroscopic', in the sense that it requires milliliter quantities for analysis. Many materials, however, would be too difficult, too expensive, or impossible to procure in the amounts required for such (macro-) rheometry. In the past decade, "microrheology" has been developed to study such materials. Rather than externally forcing a macroscopic quantity of the material, small colloidal beads are introduced and driven into (Brownian) motion by thermal forces. Because the material remains in (or close to) equilibrium, the (frequency-dependent) linear-response properties of the material can be obtained from the fluctuating probe motion using the fluctuation- dissipation theorem. This, however, suggests another limit to microrheology -- nonlinear material properties (shear thickening or thinning, yield stresses, and so on) can not be obtained using conventional techniques. Here we will discuss recent experiments in which the colloidal probe is actively driven through the material in order to probe its nonlinear response. We will address various theoretical issues in such studies -- most crucially, what exactly is being measured, and how might these measurements be interpreted to give the material information one desires?

I would principally focus on (1) the non-rectilinear path of ascent of bubbles, proposing an explanation deduced from computational results, and (2) the loss of axial symmetry of a long (Taylor) bubble rising in a vertical tube.

What is `Turbulence'? Is it the random interaction of `eddies'? Or the breakup of `big whorls into little whorls then little whorls into lesser whorls and so on to viscosity'? 40 years of observations of turbulent shear flows have revealed the presence and importance of coherent structures in the near wall regions. Those observations have led to a theory of a fundamental self-sustaining process in shear flows and the discovery of `exact coherent structures'. The latter are steady, traveling wave and periodic solutions of the Navier-Stokes equations. These solutions are unstable, yet they capture the statistics and structures of turbulent shear flows remarkably well, and force us to rethink our conventional view of turbulence.

Almost 100 years ago, it was postulated that the motor cortex should be viewed as a synthetic organ for complex motor actions such that elementary movements represented by individual motor cortical neurons could be combined in an almost infinite number of ways to generate the rich variety of complex motor actions that are ubiquitous in every day life. This view implies that motor cortex constitutes a sort of language of motor actions where individual motor cortical neurons encode the movement primitives of the language and the manner in which these neurons combine their activities to generate more complex motor actions constitute the grammar of action. Here we show that single motor cortical neurons encode time-dependent movement trajectories and not simply time-independent movement parameters. Moreover, we demonstrate that these movement trajectories can be combined using a simple addition rule when neurons fire simultaneously but independently. Finally, neurons that engage in significant synchronization combine their movement primitives through addition but with an additional gain factor which suggests that a functional role for synchronization may be to increase tuning sensitivity. Our findings are particularly topical given the recent excitement that has been generated by several studies demonstrating that electrical stimulation of motor cortex can elicit complex, time-evolving movements even at the single neuron level (Graziano et al., 2002; Brecht et al, 2004).

Ultracold quantum degenerate Fermi gases provide a remarkable opportunity to study strongly interacting fermions. In contrast to other Fermi systems, such as superconductors, neutron stars or the quark-gluon plasma of the early Universe, these gases have low densities and their interactions can be precisely controlled over an enormous range. A major goal has been the realization of superfluidity in a gas of fermions. Our observation of vortex lattices in a strongly interacting rotating Fermi gas provides definitive evidence for superfluidity. By varying the binding energy between fermion pairs, we have studied the crossover from a Bose-Einstein condensate of molecules to a Bardeen-Cooper-Schrieffer superfluid of loosely bound pairs. The crossover is associated with a new form of superfluidity. The observed transition temperatures normalized for the density of the gas by far exceed the highest transition temperatures achieved in high-T_c superconductors. We have extended those studies to interacting Fermi gases with imbalanced spin populations and observed a quantum phase transition at a critical imbalance, which is the Pauli limit of superfluidity.

Anderson's discovery of localization of waves in disordered media has profoundly affected our thinking about glasses. Glasses are by definition disordered solids, and they differ qualitatively from ordered solids. They have many more low-energy excitations and their relaxation after a disturbance extends over much longer times. The origin of these anomalies has naturally been thought to lie in their disorder. However, recent work at U of C and elsewhere suggests another origin. In addition to being disordered, glasses share another property: self-arrested mobility. The configuration is defined not by equilibrium Boltzmann probabilities or by an ad-hoc ensemble, but by succession of fluid states terminating in a jammed state where fluidity is lost. The randomness is thus defined kinetically rather than by an explicit assignment of probabilities. The extreme limit of kinetic jamming samples only a tiny subset of the jammed configurations. Only configurations immediately adjacent to fluid configurations are accessible.

This talk reviews recent progress in understanding marginally jammed solid as described in the work of Wyart, Silbert, Nagel and Witten. This work considers a system of hard spheres gradually compressed to a state of solidity. We argue that the marginally solid or jammed state is isostatic. The isostatic property is confirmed numerically. We account for several robust scaling behaviors discovered by Nagel and collaborators describing the effect of slight compression above the marginally jammed threshold. We characterize the low-frequency vibrational modes, account for the excess of near-contacts in the pair correlation function, and predict the growth of shear modulus with compression. We speculate on how the coupling of these modes might account for annealing and relaxation in glasses.

Highly correlated brain dynamics produces synchronized states with no behavioral value, while weakly correlated dynamics prevents information flow. In this talk we ask on why the brain should be critical, arguing in favor of the idea that the working brain stays at an intermediate (critical) regime characterized by power-law correlations. We discuss recent results describing the traffic between brain regions that continuously creates and reshapes complex functional networks of correlated dynamics (Phys. Rev. Lett. 94, 018102, 2005; Physica A 340, 756, 2004).

1. Liquid and gas interactions often contain bubble interactions that often include liquid films. Simulation of those liquid films is challenging since liquid films quickly become thinner than the grid resolution, which leads to premature bursting or merging of the bubbles. We prevent this thinning process to make thin film last while bubbles are interacting, obtaining a realistic animation of bubble interactions. To prevent thinning, we apply a disjoining force designed to slow down the thinning process. However, since bubbles stay longer without bursting or merging, the volume loss of each bubble is noticeable. To solve this problem, we modify the pressure projection to produce a velocity field whose divergence is controlled by the proportional and integral feedback. This allows us to preserve the volume or, if desired, to inflate or deflate the bubbles. In addition to premature bursting and volume change, another difficulty is the complicated liquid surface, which increases memory and computational costs. To reduce storage requirement, we collocate the velocity and pressure to simplify the octree mesh. To reduce the computational complexity of the pressure projection, we use a multigrid method.

2. Back and Forth Error Compensation and Correction (BFECC) was recently developed for interface computation using a level set method. We show that BFECC can be applied to reduce dissipation and diffusion encountered in a variety of advection steps, such as velocity, smoke density, and image advections on uniform and adaptive grids and on a triangulated surface. BFECC can be implemented trivially as a small modification of the first-order upwind or semi-Lagrangian integration of advection equations. It provides second-order accuracy in both space and time. When applied to level set evolution, BFECC reduces volume loss significantly. We demonstrate the benefits of this approach on image advection and on the simulation of smoke, bubbles in water, and the highly dynamic interaction between water, a solid, and air. We also apply BFECC to dye advection to visualize vector fields.

Statistical mechanics models in two dimensions and their geometrical properties at a critical point can be represented by conformally invariant random scaling curves, which are examples of the Stochastic Loewner Evolution (SLE). The same models and curves can be studied on randomly fluctuating lattices, i.e., in presence of quantum gravity. I will describe the relation between the two approaches and its application to SLE. Transmutation properties of SLEs follow from it. Fine geometrical properties of systems of random scaling curves can be obtained in this way, like those of Brownian or self-avoiding paths.

A small concentration of polymers in a turbulent channel flow can reduce the drag significantly. A physical explanation of this phenomenon and of the revelant experimental results has been a significant challenge for more than 50 years. In this talk, after a short introduction to the problem, we describe a theoretical framework to understand the phenomenon and to predict qualitatively and quantitatively the experimental data.

We present the results of Direct Numerical Simulations (DNS) of turbulent flows seeded with millions of passive inertial particles. The maximum Reynolds number is $Re_{\lambda } \sim 200$. We study the case of particles much heavier than the carrier flows in the limit when the Stokes drag force dominates their dynamical evolution. We study both the transient and the stationary regimes. In the transient regime, we study the growth of inhomogeneities in the particle spatial distribution driven by the preferential concentration out of intense vortex filaments. In the stationary regime, we study the acceleration fluctuations as a function of the Stokes number in the range $St \in [0.16:3]$. We also compare our results with those of pure fluid tracers ($St=0$) and we show the almost singular behaviour of inertia for small Stokes values. Starting from the pure monodispersed statistics we also present a first attempt to characterized polydispersed suspensions with a given mean Stokes, $\overline{St}$.

Materials without crystalline order undergo plastic deformation in ways both similar and fundamentally different from their crystalline counterparts. In this talk I will review the theoretical models typically used to model the micromechanics of deformation in this class of solids. I will then discuss the ways in which molecular simulations do and do not agree with these theories.

In particular, molecular dynamics simulations of a number of amorphous systems analogous to metallic glasses reveal the structural changes that accompany plastic deformation and localization involve a decrease in the local short range ordering. We have simulated both two-dimensional and three-dimensional systems in nanoindentation [1], uniaxial tension [2] and compression [3] in plane strain. The degree of strain localization depends sensitively on the quench rate during sample preparation, with localization only arising in more gradually quenched samples. Careful analysis of the strain rate dependence of the localization allows us to extrapolate to the low strain rate limit. This analysis reveals a transition from localized flow to homogeneous flow at a critical value of the potential energy per atom prior to testing. This transition occurs in both two- and three- dimensional systems. The transition appears to be associated with the k-core percolation of short range order (SRO) in the two-dimensional system [2]. A generalization of the Frank-Kasper criterion permits the identification of SRO in the three-dimensional systems. Only in certain systems does this method predict a percolation transition corresponding to the transition in mechanical behavior [3]. I will discuss the non-uniqueness of this measure of SRO, and consider whether a more rigorous definition could be derived which applies to systems far from the hard-sphere limit. Recent results regarding the dynamics of shear localization will be discussed if time permits.

[1] Y. Shi and M.L. Falk, "Structural transformation and localization during simulated nanoindentation of a non-crystalline metal film," Applied Physics Letters, Vol. 86, pp. 011914 (2005).

[2] Y. Shi and M.L. Falk, "Strain localization and percolation of stable structure in amorphous solids," Physical Review Letters, Vol. 95, pp. 095502 (2005).

[3] Y. Shi and M.L. Falk, "Atomic-scale simulations of strain localization in three-dimensional model amorphous solids," Physical Review B, in press.

Combinatorial games, which include chess, Go, checkers, Nim, Chomp, and dots-and-boxes, have both captivated and challenged mathematicians, computer scientists, and players alike. In this talk I will report on a new physics-inspired approach that reveals surprising connections between combinatorial games and key ideas from physics and nonlinear dynamics, most notably notions of scaling, renormalization, universality, and chaotic attractors. Using the game of Chomp as a prototype (which is one of the simplest of the "unsolved" combinatorial games), we find that there is an invariant geometric structure underlying the game that "grows" (reminiscent of crystal growth), and show how this growth may be analyzed using a renormalization technique. This in turn allows one to calculate detailed, probabilistic properties of the winning and losing positions of the game, answers longstanding questions that have appeared in the literature, and suggests a natural pathway toward a new class of algorithms for combinatorial games.

Particles suspended in a complex fluid can be subject to a variety of interactions including electromagnetic, elastic, entropic, and interfacial forces. The study of these forces has provided understanding of fundamental problems in fluid physics as well as exciting avenues for applications. For example, nematic liquid crystals are complex fluids possessing anisotropy that introduces both forces and torques on a suspended particle. Nematics, which are comprised of rod-like molecules, are characterized by an alignment of the long axes of the molecules. Anchoring of the alignment direction at a suspended particle's surface introduces boundary conditions on the alignment that obligate distortions with a corresponding cost in elastic energy. The tendency to minimize this energy leads to forces on the particles. This talk will focus on our studies to measure quantitatively such forces on highly anisotropic, wire-shaped particles and to control these forces in order to manipulate the particles. The talk will also describe recent experiments investigating the dynamical behavior of the wire-shaped colloids in strongly non-Newtonian surfactant solutions that display shear-induced nematic order.

Small particles floating on a turbulent fluid behave very differently than those that are neutrally buoyant. The floaters sample the velocity field at the surface but cannot follow local vertical velocity fluctuations in and out of the bulk. For that reason they form a compressible system and are seen to coagulate into string-like structures. The rate of change of the entropy of the floaters dS/dt is measured and compared with theoretical predictions and computer simulations. This rate is a random variable that takes on positive and negative values corresponding to coagulation and dispersion. Its measurement permits a test of the Fluctuation Relation of Gallavotti and Cohen.

It is well known that small neutral particles normally tend to aggregate due to the van der Waals forces. We discover a new universal long-range interaction between solid objects in polymer media that is directly opposite the van der Waals attraction. The new force could reverse the sign of the net interaction, leading to the net repulsion. This universal repulsion comes from the subtracted soft fluctuation modes, which are not present in the real polymer system, but rather are in its ideal counterpart. The predicted effect has a deep relation to the classical Casimir interactions, providing an unusual example of fluctuation-induced repulsion instead of normal attraction. That is why it is referred to as the Anti-Casimir effect. We also find that the correlation function of monomer units in a concentrated solution of long polymer chains follows a power-law rather than an exponential decay at large distances.

First I shall review spreading phenomena in statistical physics - percolation, directed percolation, sign percolation... - and discuss the types of transitions observed in these systems. Then I'll show that similar phenomena occur in knowledge networks and propagation algorithms.

Viruses present one of the most elegant examples of spontaneous self-assembly provided by nature. They can be produced both in the lab and in the living cells, with the highest degree of monodispersity. This aspect alone brings crucial amount of interest in virus self-assembly. In this talk we address electrostatic interactions inside RNA viruses, and, in particular, interactions between genome and protein tails. By mapping the problem onto complexation between charged polymers, we can predict properties such as spacial organization of the genome and constraints on the genome length. For example, it is a common belief that the genomic code uniquely determines protein sequence and the ultimate biological structures. We will argue that the reverse relation may also be true, and the virus genome is constrained in length to minimize electrostatic energy. This is found to be particularly true in wild type viruses that have undergone long periods of mutations.

It is known since Bachelier 1900 that price changes are nearly uncorrelated, leading to a random-walk like behaviour of prices. However, compared to the simplest Brownian motion, price statistics reveal a large number of anomalies, such as fat tails and long memory in the volatility. The detailed study of trade by trade and order book data allows one to provide evidence for a subtle compensation mechanism that underlies the `random' nature of price changes. This compensation drives the market close to a critical point, which may explain the sensitivity of financial markets to small perturbations, and their propensity to enter bubbles and crashes. We argue that the resulting unpredictability of price changes is quite far from the neo-classical view that markets are informationally efficient.

Why don't glasses flow? An old explanation, yet unproven experimentally, is that the dynamics become sluggish in supercooled liquids, dense colloids, and granular assemblies because increasingly larger regions of the material have to move simultaneously to allow flow. We review recent physical arguments, theoretical models and experimental tools that suggest the existence of an underlying cooperative length that grows upon approaching the glass transition.

We will summarize recent progress on the distribution of eigenvalues (or singular values) of random correlation matrices, and their relevance to portfolio optimisation and econometric forecast. Some new results will be presented, in particular concerning the case of generic (rectangular) correlation matrices, and the statistics of the top eigenvalue in the presence of heavy tailed noise.

I got my Ph.D. for simulations of granular materials at U. Chicago, and yet now I am the Staff Director of the Research Subcommittee of the Committee on Science in the U.S. House of Representatives. Issues under the purview of the Research Subcommittee include oversight of the National Science Foundation, nanotechnology, information technology research, including cybersecurity, homeland security research, and math and science education at all levels. The talk will cover why I am no longer a practicing scientist, how I made the transition, and what it is like working on science policy in Washington, including what kinds of jobs ex-scientists have in DC. I will also touch on how Congress works and how it affects agencies of interest to materials researchers (such as NSF). I can also talk about the status of relevant bills and funding of science agencies and take questions on specific policy issues.

Biological regulatory networks are capable of sophisticated functions, such as integrating chemical signals, storing memories of previous molecular events, and keeping time. It is well-known that many regulatory proteins in these circuits form dimers and higher-order complexes. In my talk, I will discuss two important consequences of dimerization. First, ample experimental evidence suggests that protein subunits in vivo can degrade less rapidly when associated in complexes. This effect leads to a concentration dependence in the protein degradation rate, and our theoretical work demonstrates how this effect can enhance the function of bistable and oscillatory circuits. Second, active proteins can often be sequestered into inactive complexes. This "molecular titration" can lead to strong nonlinearities, and suggests a scenario for the rapid evolution of bistable or oscillatory circuits in nature.

There have been several attempts to construct statistical mechanical descriptions of athermal particulate systems, for example the Edward's entropy description for granular materials. Tapping experiments by Nowak, et al. (Phys. Rev. E, 57 (1998) 1971) and numerical simulations of granular shear flow by Makse, et al. (Nature 415 (2002) 614) have shown that the Edward's description may be promising for slow, dense granular flows. An essential assumption of the Edward's framework is that all jammed configurations are equally likely. However, this assumption has not been explicitly tested. Using numerical simulations, we create jammed hard particle packings using two experimentally relevant protocols: 1) a compression and decompression scheme and 2) a quasi-static shear flow. For both methods, we find that jammed packings are not equally likely, and thus we argue that the Edward's entropy description for granular materials should be reconsidered.

In traditional interpretations of quantum mechanics, the Born probability rule was introduced by fiat at an explicit or implicit 'collapse' process, outside the known dynamical equations. Attempts to formulate such collapse processes explicitly have not produced appealing theories. In recent years, many-worlds interpretations which avoid such processes have become popular. I present old arguments that the Born probability rule is unnatural within standard many-worlds accounts, which would appear to lead to very unfamiliar probabilities. I then present an idea by Hanson, which might possibly account for Born probabilities as actual ratios of numbers of experiencable worlds within standard quantum dynamics. In view of difficulties with that idea, I show that relatively palatable non-linear modifications of quantum dynamics could give rise to the proper ratios of numbers of outcomes without any fine-tuning.

The local structure of biological networks can be studied by "counting" network motifs. Although the number of possible motifs with 8 or more nodes becomes overwhelming, it is possible to study large-size network patterns if we focus on specific motifs such as cycles. Cycles are interesting because in directed graphs they can form feedback and feed-forward loops, which usually have important dynamic functions in biological pathways. We studied large-size cycles and characterized their statistical properties in different networks. Cycles can be studied as a one-dimensional (slightly generalized) Ising model, with edges representing spins. It turns out that the statistical ensembe of this Ising model accounts for many of the statistical properties observed in the cycles for all networks studied. We found that for each network, two parameters in the Ising model, the nearest-neighbor coupling constant J and a chemical potential for undirected links m, are enough to account for the ensemble characteristics of cycles of any size between 3 and 20. In most biological networks studied, the fitted-coupling parameter J of the Ising model is sufficiently negative that there is a clear "anti-ferromagnetic order" which in terms of network motifs implies that there is a considerable depletion of feedback loops and selection for bifan-like cycles. This may have important signal processing implications, as will be exemplified in a particular cellular signal transduction network.

This work done in collaboration with Avi Ma'ayan, Guillermo Cecchi, John Wagner, Ravi Rao and Ravi Iyengar.

Systems of heterogeneous agents often display collective properties that cannot be deduced in a simple way from the behaviour of the individual. There are many examples of these systems in biology, such as bacterial colonies, fish schools, insects swarms, starling flocks and mammals herds. In particular, the coordinated patterns displayed by starlings before roosting time are a fascinating phenomenon whose intrinsic microscopic mechanisms are still unknown. In this talk I will present the first results of a highly interdisciplinary research project, whose aim is understanding collective motion in organic systems, from the case study of starling flocks to, eventually, herding behaviour in socio-economic contexts.

I will focus on the most innovative part of our research, namely the experimental reconstruction of the tridimensional positions and trajectories of individual birds during flocking. To this aim, we performed a non-trivial stereoscopic analysis of sets of digital images taken at high resolution and frequency with an appropriately calibrated apparatus. The results of this analysis can be compared with the predictions of existing models and represent the starting point for further modeling of collective motion and its biological interpretation.

Granular media consist of macroscopic, athermal particles that ``jam'',

into a solid-like state when subjected to a confining pressure. Recent studies of this jamming transition in systems of frictionless particles have shown, quite remarkably, that the jamming point has many features of a critical point, exhibiting power law scalings of various quantities nearby. We study the origin of this scaling behavior by analyzing the linear response of these packings to mechanical perturbations. The response to local forcing fluctuates over a length scale that diverges at the jamming transition. The response to global shear or compression becomes increasingly non-affine near the jamming transition. This is due to the proximity of floppy modes, the influence of which we characterize by the relative displacements of neighboring particles. We show that the local response also governs the anomalous scaling of elastic constants and contact number. If time permits I will shortly discuss the consequences of adding friction to the interaction between the particles.

The locomotion of most fish and birds is realized by flapping wings or fins transverse to the direction of travel. Here, we study experimentally the dynamics of a wing that is "flapped" up and down but is free to move in the horizontal direction. In this table-top prototype experiment, we show that flapping flight occurs abruptly at a critical flapping frequency as a symmetry-breaking bifurcation. We then investigate the separate effects of the flapping frequency, the flapping amplitude, the wing geometry and the influence from the solid boundaries nearby. Through dimensional analysis, we found that there are two dimensionless parameters well describe this intriguing problem that deals with fluid-solid interaction. The first one is the dynamical aspect ratio that combines four length scales, which includes the wing geometry and the flapping amplitude. The second parameter, the Strouhal number, relates the flapping efforts to it resultant forward flight speed. Overall, we emphasize the robustness of the thrust-generating mechanisms determining the forward flight speed of a flapping wing, as observed in our experiments.

The modeling of transcriptional regulation of genes in cells relies on representations of dynamical processes that occur in complex networks of interacting elements. A starting point for understanding such processes is the analysis of large random networks of Boolean gates. A theory of the "order-chaos" phase transition in such networks reveals surprising dynamical structures, which I will explain. Though Boolean logic is an intuitively appealing framework for describing transcriptional interactions, care must be taken to separate generic network behavior from artefacts of the Boolean model. I will discuss the relation between attractors of synchronous and asynchronous dynamics in Boolean networks and the continuous dynamics that arise in more realistic models of transcriptional networks.

Recent observations of rapid changes within the Greenland and West Antarctic Ice Sheets indicate that ice sheets are far more dynamic than many glaciologists would have predicted only a decade ago. At present ice-sheet models used in climate-change assessments, such as the IPCC reports, lack the physics required to capture these rapid changes. Given the impact that variations in ice-sheet volume have on sea level, it is critical that improved ice-sheet models be developed soon. I will touch on some of the mechanisms of rapid change in ice sheets, focusing on the buttressing role of ice shelves. In addition, I will discuss the near-term future of computational glaciology, and why some have labeled the present as the "golden age of glaciology".

The Earth's magnetic field is continually regenerated by dynamo action in the liquid iron core. Numerical models for this process first achieved self-sustaining magnetic fields about ten years ago, and the results have been spectacular. Models have successfully reproduced important features of the Earth's magnetic field, including the dipole dominance and the episodic reversal of polarity. However, it is generally acknowledged that these models are unrealistic in many respects. All of the models currently use physical properties that are very far from Earth-like values. As a consequence, the nature of the dynamics is altered and the potential to address important geophysical questions is limited. The challenge for making improvements lies in dealing with the effects of unresolved flow. Simple models based on eddy diffusion are probably inadequate because the influences of rotation and a strong magnetic field make the small-scale flow highly anisotropic. Alternative strategies that reproduce the expected anisotropy and evolve with the large-scale fields are described. Encouraging results are presented for both plane-layer and spherical-shell dynamo models and a summary of the outstanding challenges is given.

Cell migration is an essential process involved in many key functions of normal physiology and disease including cellular development in embryogenesis, neuronal growth, cancer metastasis or tumor invasion, and tissue repair in wound healing or immune response. Fluorescent Speckle Microscopy (FSM) is a new live cell imaging technique for probing the molecular regulation mechanisms of this process. Time-lapse FSM images of fluorescently labeled proteins in live cells contain a rich set of information about the dynamics of the target protein structure. In this talk, I will first give you an introduction to cell migration and this new imaging technique. I will then show you how multi-dimensional data can be extracted from raw FSM movies focusing on the reconstruction of intracellular forces. In the end, examples will be given to demonstrate how advanced analysis of these data and mathematical modeling make it possible to do quantitative study of the regulation mechanisms of cellular functions at the molecular level.

Both the `reverse engineering' of biological networks (for example, by integrating sequence data and expression data) and the analysis of their underlying design (by revealing the evolutionary mechanisms responsible for the resulting topologies) can be re-cast as problems in classification: predicting a categorical label in high-dimensional feature spaces. In the case of inferring biological networks, predicting up- or down- regulation of genes allows us to learn ab intio the transcription factor binding sites (or `motifs') and to generate a predictive model of transcriptional regulation. In the case of revealing evolutionary designs, quantitative, unambiguous model validation can be performed, clarifying which of several possible theoretical models of how biological networks evolve might best (or worst) describe real-world networks. In either case, by taking a machine learning approach, we statistically validate the models both on held-out data and via randomizations of the original dataset to assess statistical significance. By allowing the data to decide which features are the most important (based on predictive power rather than overabundance relative to an assumed null model) we learn models which are both statically validated and biologically interpretable. 'References':

1) Manuel Middendorf, Anshul Kundaje, Chris Wiggins, Yoav Freund, and Christina Leslie. Predicting genetic regulatory response using classification. ISMB 2004; q-bio/0411028

2) Manuel Middendorf, Anshul Kundaje, Mihir Shah, Yoav Freund, Chris H. Wiggins, and Christina Leslie. Motif discovery through predictive modeling of gene regulation. RECOMB 2005.

3) M. Middendorf, E. Ziv, and C. H. Wiggins. Inferring network mechanisms: the drosophila melanogaster protein interaction network. PNAS 2005; q-bio/0408010.

4) Manuel Middendorf, et al. Discriminative topological features reveal biological network mechanisms. BMC Bioinformatics 2004; q-bio/0402017.

Discrete droplets offer significant advantages over single-phase flows in the design of some microfluidics-based biochemical assays. To realize these advantages, fundamental operations must be controlled and optimized, including manipulation of reactor volume, encapsulation, merging, mixing, and detection. In this presentation we address some current limitations in these processes, particularly that in which the minimum droplet size is restricted by the device geometry. We show that the presence of surfactants at the liquid-liquid interface leads to the formation of micron-scale and smaller threads at a flow-focusing junction. Threads stretch and break into picoliter droplets. The process is sustained in a specific range of flow rates and surfactant concentrations. Analysis of the mechano-chemical coupling between flow and surfactant transport at these length scales suggests ways to tailor the process for future devices.

The transformation of a narrow beam into a hollow cone when incident along the optic axis of a biaxial crystal, predicted by Hamilton in 1832, created a sensation when observed by Lloyd soon afterwards. It was possibly the earliest prediction of a qualitiatively new phenmenon using mathematics, and the prototype of the conical intersections reflecting the degeneracy structure of families of matrices, now popular in quantum chemistry. But the fine structure of the light cone contains many subtle features, slowly revealed by experiment, whose definitive explanation, involving new mathematical asymptotics, has been achieved only recently, along with definitive experimental test of the theory. Radically different phenomena arise when chirality and absorption are incorporated in addition to biaxiality.

Flagellated bacteria, such as E. Coli, propel themselves using multiple flagella - long, thin helical filaments - that are rotated using nanoscale motors. We will discuss several aspects of the fluid mechanics associated with bacterial motility, studied using scale modeling, numerical simulations and microscale experiments. The phenomena explored include the mechanics of flagellar bundling, in which several distinct filaments combine into a single helical bundle via viscous hydrodynamic interactions, the flow fields associated with viscous helical motions, and mechanisms for hydrodynamic synchronization of adjacent flagella motion. We will also show how the flagella motion can be harnessed in engineered systems to enhance low Reynolds number mixing, to pump fluids, and to transport objects through microfluidic systems.

In the popular imagination, quantum computers would be almost magical devices, able to "solve impossible problems in an instant" by trying exponentially many solutions in parallel. In this talk, I'll describe four results in quantum computing theory that directly challenge this view.

First, I'll show that any quantum algorithm to decide whether a function f:[n]->[n] is one-to-one or two-to-one needs to query the function at least n^{1/5} times. This provides strong evidence that collision-resistant hash functions, and hence secure electronic commerce, would still be possible in a world with quantum computers.

Second, I'll show that in the "black-box" or "oracle" model that we know how to analyze, quantum computers could not solve NP-complete problems in polynomial time, even with the help of nonuniform "quantum advice states.",

Third, I'll show that quantum computers need exponential time to find local optima -- and surprisingly, that the ideas used to prove this result also yield new classical lower bounds for the same problem.

Finally, I'll show how to do "pretty-good quantum state tomography",

using a number of measurements that increases only linearly, not exponentially, with the number of qubits. This illustrates how one can sometimes turn the limitations of computational devices on their head, and use them to develop new techniques for experimentalists.

No quantum computing background is assumed.

Several of the deepest principles in physics can be seen as limits on 'technology': for example, the Second Law of Thermodynamics and the impossibility of superluminal communication. In this talk, I'll ask whether the hardness of NP-complete computational problems would likewise be useful to assume as a physical principle. To investigate this question, I'll study the computational effects of living in a universe with closed timelike curves, a universe where the Schroedinger equation was nonlinear, a universe with particular many-particle entangled states left over from the Big Bang, or a universe where you could kill yourself with some probability and then 'postselect' on remaining alive. I'll show that one can make definite, nontrivial statements about what problems could be efficiently solved in each of these universes -- and also about what problems still couldn't be.

Colloidal suspensions consist of micron sized solid particles suspended in a solvent. The particles are Brownian so that the suspension as a whole behaves as a thermal system governed by the laws of statistical mechanics. For example at high volume fractions, mono-dispersed suspensions will crystallize. If the number density of particles is reduced, such crystals will undergo a thermodynamic melting transition. The thermodynamic nature of these systems has allowed scientists to use colloidal suspensions as models for investigating numerous processes that typically take place on the atomic scale but are often very difficult to investigate. In this talk I will describe the experimental techniques we use to investigate the 3D structure and dynamics of these systems as well as review experiments we have conducted aimed at understanding defect nucleation, translation, and entanglement in colloidal crystals. I will then describe ongoing experiments aimed at elucidating various non-equilibrium processes such as the epitaxial growth of thin films and various lubrication phenomena.

The activity of neurons in an area of the brain referred to as primary motor cortex provides the signals that control the ability to execute movements. One of the crucial questions, still unresolved, is that of identifying the code used by this neural ensemble. We address this question through the analysis of data obtained for an awake behaving monkey. An implanted multielectrode array records the activity of about one hundred neurons in primary motor cortex during the execution of a sequence of straight reaches to nearby targets. A natural representation for the ensemble activity is provided by a high-dimensional space in which each axis represents the activity of a single neuron as an independent degree of freedom. However, the observed correlations among neurons whose activity is detectably modulated by the task suggest that the population defines a low-dimensional space within the high-dimensional space of independent firing activities. We have used linear and nonlinear methods for dimensionality reduction to find the low-dimensional structure that captures the underlying relationship between population neural activity and behavioral task. The use of multidimensional scaling in conjunction with an empirical measure of geodesic distances yields a low-dimensional manifold whose intrinsic coordinates capture the geometry of the task in the external physical space.

Cosmological observations of the distant universe are usually interpreted to imply either the existence of "dark energy" or indications of a breakdown in general relativity. In the talk I will discuss a third approach: nonlinear dynamics of the expansion history of the universe are more complicated than usually assumed.

Over the last ten years more than a dozen mammalian whole genomes have been fully sequenced, providing a digital library of unprecedented scope and detail and posing new challenges in decoding the information contained therein. At the same time, experimental biology has been revolutionized by the discovery of non-coding RNA, termed "biological dark matter" in the popular media. I describe how these developments are unified in what may well be the first time that scale invariance, long a cornerstone of modern physics, establishes for itself a central and essential role in molecular biology, evolution, and medicine [1]. Application of these ideas to the discovery of new microRNAs in mouse embryonic stem cells is discussed, and if time, the first massively parallel sequencing of the short RNome of mouse stem cells will be reported.

[1] W Salerno, P Havlak, and J Miller (2006). Scale-invariant structure of whole-genome intersections and alignments. Proc Natl Acad Sci USA, 103(35): p. 13121-5.

The collision of two black holes is thought to be one of the most energetic events in the universe, emitting in gravitational waves as much as 5-10% of the rest mass energy of the system. An international effort is currently underway to detect gravitational waves from black hole collisions and other cataclysmic events in the universe. The early success of the detectors will rely on the matched filtering technique to extract what are, by the time the waves reach earth, very weak distortions in the local geometry of space and time. In the case of black hole mergers numerical simulations are needed to obtain predictions of waveforms during the final stages of coalescence. 2005 was a watershed year for numerical simulations of black holes, and we are now beginning to explore the fascinating landscape of black hole collisions in the fully non-linear regime of Einstein's theory. In this talk I will describe the computational challenges and techniques required to simulate black holes within the framework of Einstein's theory of general relativity, and present results form recent successful simulations of black hole coalescence.

For its molecular simplicity, ice is an exceedingly complex system and is one of the most fascinating material in the world of condensed matter physics. For example, it is known to possess non-trivial proton dynamics and residual disorder and entropy well below the freezing point of water. Theoretically, such entropy, originally estimated by Linus Pauling in 1935, arises from the extremely large number of ways of arranging for the two short and two long proton bond lengths surrounding each oxygen ion. It has recently been found that there exist a remarkable analogy between the statistical physics of certain geometrically frustrated magnetic materials and the problem of proton ordering in ice, hence the name "spin ice". In this talk I will briefly review the broad problem of frustration in condensed matter physics. I will then discuss the discovery of spin ice materials and highlight some of the interesting experimental and theoretical developments surrounding the "spin ice" problem over the past ten years or so and discuss some of the current open questions.

The Euler equations, describing a potential flow of infinitely deep 2-D ideal incompressible fluid with free surface, takes a compact closed form after the conformal mapping of the domain filled with fluid up to the lower half-plane. The "conformal" evolution equations of surface dynamics are suitable both for analytic study and numerical simulation. The main tool of analytic investigation is the consideration of singularity dynamics in the upper half-plane. In a typical situation the singularities are the moving and broadening cuts. As far as the cuts are narrow, the problem can be solved analytically. It describes the formation of drops and shapes of surface, similar to the "Saffman fingers". A certain class of initial data can be described approximately by the famous Laplace Growth Equation (LGE). In this and even more general cases the conformal evolutionary equations have "extra" constants of motion, which are not connected with natural symmetries of the system. It leads to conjecture that the system in completely integrable but this question is still open.

The conformal equations could be efficiently solved numerically by the use of the spectral code. We elaborated a comfortable and stable numeric algorithm making possible to model the nonlinear wave propagation during a very long time (up to 100 000 periods). We performed long-time modeling of nonlinear stage of the Stokes wave modulational instability and found that the instability leads to formation of solitonic turbulence and finally, to the appearance of freak waves.

In granular materials, or other spatially disordered systems such as colloidal glasses, gels, and foams, in which thermal fluctuations are believed to be negligible, a jamming transition has been proposed: upon increasing the volume density (or "packing fraction") of particles above a critical value, the sudden appearance of a finite shear stiffness signals a transition between flowing liquid and rigid (but disordered) solid states. We carry out numerical simulations of a soft sphere model of a granular material in two dimensions at zero temperature, computing the shear viscosity of the flowing state as a function of both particle volume density and applied shear stress. About the jamming transition we find an excellent scaling collapse of our data to a function of a single scaling variable. By considering velocity correlations we extract a correlation length and show that it too obeys a scaling collapse, diverging at the jamming transition. Our results confirm that jamming is a true second order critical phenomenon that, as originally proposed by Liu and Nagel, extends to driven steady states along the non-equilibrium axis of applied shear stress.

Most of the interesting things that happen in living organisms require interactions among many components, and it is convenient to think of these as a "network" of interactions. We use this language at the level of single molecules (the network of interactions among amino acids that determine protein structure), single cells (the network of protein-DNA interactions responsible for the regulation of gene expression), and complex multicellular organisms (the networks of neurons in our brain). In this talk I'll try to look at two very different kinds of theoretical physics problems that arise in thinking about such networks. The first problems are phenomenological: Given what our experimentalist friends can measure, can we generate a global view of network function and dynamics? I'll argue that maximum entropy methods can be useful here, and show how such methods have been used in very recent work on networks of neurons, enzymes, genes, and (in disguise) amino acids. In this line of reasoning there are of course interesting connections to statistical mechanics, and we'll see that natural statistical mechanics questions about the underlying models actually teach us something about how the real biological system works, in ways that will be tested through new experiments. In the second half of the talk I'll ask if there are principles from which we might actually be able to predict the structure and dynamics of biological networks. I'll focus on optimization principles, in particular the optimization of information flow in transcriptional regulation. Even setting up these arguments forces us to think critically about our understanding of the signals, specificity and noise in these systems, all current topics of research. Although we don't know if we have the right principles, trying to work out the consequences of such optimization again suggests new experiments.

Two-dimensional conformally invariant systems are scale-invariant systems with local interactions, such as, for example, critical statistical systems. Domain walls in them are fluctuating fractal curves. The study of the shape of these curves is a recent development in critical phenomena. I will show how these curves are related to quantum Gaussian field theory and how their fractal spectrum is found using this field theory.

Two different physical realizations of turbulent flows will be reviewed: shear turbulence and natural convection. We will discuss how the statistical properties of turbulence fluctuations are affected by the presence of important underlying velocity or thermal gradients; implications range from the quest to the "ultimate state of thermal convection," as predicted by Kraichnan in 1962, to the improvement of eddy viscosity models close to wall boundaries.

Molecular dynamics simulations are used to investigate driven nano-scale flows of liquids along open "chemical channels": patterns of completely-wetting solid embedded in a planar substrate, and sandwiched between less wetting solid regions. Liquid placed atop a long straight wetting stripe evolves into connected "pearls," due to a Rayleigh-like surface tension instability, which propagate and merge when a pressure gradient is applied. In more complicated wetting patterns involving dividing and combining junctions, propagating pearls again appear, and exhibit intriguing stability and bifurcation behavior when the liquid flows. The numerical results in the straight-channel case are compared to a simple long-wavelength approximation and a full stability analysis based on the Stokes equations. The different approaches are qualitatively but not quantitatively consistent, which we attribute to the presence of a broad interfacial region and substantial thermal fluctuations.

Nanomaterials, such as block copolymeric membranes and nanodiamonds, can be engineered for controlled and localized drug delivery via implantable devices. Inflammatory responses against these implants, however, can result in degradation and rejection of these devices.

Our laboratory has developed a 'nano-cloaking' technology via copolymer/nanodiamond functionalization with anti-inflammatory and chemotherapeutic molecules. This technique has allowed the platform materials to serve as broadly applicable therapeutic delivery systems. These NanoCloak's dramatically inhibited inflammatory responses in vitro. Furthermore, in vivo studies using copolymeric interfaces showed that NanoCloak enables implant cloaking in an animal model which is envisioned to significantly impact the chronicity of implant functionality.

We also interrogated the cyto-regulatory networks via cytokine expression levels (IL-6, TNF?, iNOS) via quantitative PCR and found that the copolymers/nanodiamonds interface well with their surrounding biological environment at a genetic level. Monitoring of internal cellular processes as well as cytokine release at the tissue-nanomaterial interface revealed the absence of basal cellular inflammatory responses.

Dr. Dean Ho is currently an Assistant Professor in the Departments of Biomedical Engineering and Mechanical Engineering in the Robert R. McCormick School of Engineering and Applied Science and Member of the Robert H. Lurie Comprehensive Cancer Center at the Feinberg School of Medicine at Northwestern University where he directs the Laboratory for Nanoscale Biotic-Abiotic Systems Engineering (N-BASE). He completed his Ph.D. in Biomedical Engineering at UCLA, and was a Research Associate in the Departments of Electrical Engineering and Bioengineering at the California Institute of Technology as well as in the UCLA Mechanical and Aerospace Engineering Department from 2005-2006.

Close-packed nanoparticles separated by short spacer molecules form a new class of solids with unique behavior that arises from the interplay of nanoscale confinement and tunable coupling. I will discuss experiments performed by our group on the ultrathin limit of such solids, a single layer of close-packed metal nanoparticles. It turns out that such layers can be self-assembled with very high degree of structural order by a simple drying mechanism. With inter-particle spacings of 1-2nm, electrons can tunnel across these layers and the resulting nonlinear current-voltage characteristics reflect strong Coulomb blockade effects. Surprisingly, the short molecular spacers also provide for tensile strength and the layers can be draped over holes, forming flexible membranes of remarkable resilience.

The fabrication and properties of semiconductor quantum dots has received significant attention in recent years due to their potential application in a wide range of nanoscale integrated systems (diodes, filters, etc). One feature of quantum dots is that they can form spontaneously, or self-assemble, as the result of an instability when a thin solid film is deposited onto a solid substrate. We first investigate the self-assembly of quantum dots in a thin solid film caused by epitaxial stress and wetting interactions between the film and the substrate. We derive an evolution equation that governs the shape of the film surface and show that the presence of wetting interactions can lead to the formation of spatially regular arrays of quantum dots. We then consider the growth of a thin solid film by molecular beam epitaxy which precedes the formation of quantum dots. For the case of Levy flights, we develop the analog theory of step-flow growth and determine the step-flow velocity as a function of the terrace length.

When a bubble (or drop) is placed in a strong viscous flow (e.g. a shear flow), it develops very sharp tips at its ends. Similarly sharp structures occur when a viscous fluid is sucked away from its interface with the ambient air (selective withdrawal). We have constructed a code to solve for stationary solutions of the flow equations for arbitrary viscosity ratios, both for the drop and the selective withdrawal geometry. The code resolves tip curvatures of more than $10^8$ times the bubble radius. We compare the shape and stability of drops to an earlier theory by Taylor (1964). We then focus on the highly curved tip region, not considered by Taylor. We find that the shape near the tip is universal, i.e. independent of the driving flow and of the geometry of the interface. A similar statement applies to the stability of solutions, which is controlled by the viscosity ratio. This leaves open major questions as to the proper interpretation of recent experiments in the selective withdrawal geometry.

A granular material is a large conglomeration of discrete macroscopic particles. It has unique properties different from other familiar forms of matter. One of the most interesting properties of a granular material is the absence of the cohesive force between its component particles, and a flow of such a material can be seen as a special "fluid",

with zero surface-tension. We explored this aspect of granular flow in two specific experiments. First, we performed the granular analog to "water bell" experiments. When a wide jet of granular material impacts on a fixed cylindrical target, it deforms into a sharply-defined sheet or cone with a shape that mimics a liquid with zero surface tension. The jets' particulate nature appears when the number of particles in the beam cross-section is decreased: the emerging structures broaden, gradually disintegrating into diffuse sprays. The experiment has a counterpart in the behavior of quark-gluon plasmas generated by colliding heavy ions in RHIC, where a high collision density gives rise to collective behavior also described as a liquid. Second, we performed granular analog of viscous fingering experiments in the Hele-Shaw geometry. In the absence of surface tension, the ordinary viscous fingering is expected to be singular. However, it is hard, if not impossible, to realize this with normal fluids. We showed that near the yield stress of a granular flow, the grain/gas interface exhibits a fractal structure and local cusps, both suggestive of a finite time singularity. Furthermore, we find a novel scaling law for fingering width as compared with normal fluid fingering.

Adult songbirds transmit specific songs to juveniles who then train their own song production systems to mimic the adult song. The neural and auditory bases for this cultural behavior are known in broad, qualitative outline to be associated with identified collections of neurons in the male songbird brain and the bird's auditory apparatus. The overall song learning, training, and production system is straightforward enough that one can expect to develop a quantitative set of models with increasing complexity and resolution. These would allow the prediction of new phenomena in the song system as well as provide an integrated view of existing observations.

We will outline some of the established aspects of the songbird nervous/auditory system and describe our efforts to develop a "coarse grained" computational description of its function. We will also describe ingredients missing at present with an optimistic eye toward how we need to proceed to their incorporation. To proceed from a coarse grained account we will need both additional anatomical and electrophysiological information as well as computational development of models.

A suggestion for developing and verifying the needed models will be outlined. The method is applicable to networks in many arenas of physics and biological physics. It is computationally demanding.

A role for physicists in providing quantitative computational models of this functional nervous system and others, perhaps more complex, will be discussed.

We poorly understand the microscopic properties of amorphous solids, such as transport, force propagation, or even the nature of their mechanical stability. These questions are related to the presence of soft modes in their vibrational spectrum. We explain the nature of these modes in repulsive, short-range systems. This enables to derive a microscopic criterion of rigidity which extends a previous result of Maxwell. This implies that rigidity is not a local property, but is characterized by a length which depends on the packing geometry, and which can be large and even diverge, e.g. near the random close packing. We argue that this description applies to granular media, silica and colloidal glasses. We propose a description of the glass transition in hard sphere systems in terms of these soft modes. This leads to several predictions, in particular a non-trivial power law scaling characterizing the packing geometry in the glass phase, that we check numerically.

Granular and continuous materials fail in fundamentally different ways, yet inherently discontinuous natural fault materials have often been modeled as continuum processes. I will present the results of laboratory experiments which complement existing numerical simulations, rock mechanics experiments, seismological observations, and geologic studies to highlight the granular conrols on fault behavior. We perform experiments in a quasi-two-dimensional shear zone containing several thousand 5 mm circular and elliptical photoelastic plastic disks, allowing us to monitor the spatiotemporal evolution of both internal stress and strain. While the time, length, and strength scales are vastly different from the natural case, the frictional behvior is found to be in agreement. Therefore, the experiments allow us to isolate the effects of granular interactions and choice of boundary conditions on the fault behavior, through the observation of large populations of stick-slip and creep events.

The Method of Maximum Likelihood is a standard of modern statistical analysis: it is generally the first and often the last choice of analysts when choosing among models with imperfect data. The theory of maximum likelihood is very beautiful: a conceptually simple approach to an amazingly broad collection of problems. This theory provides a simple recipe that purports to lead to the optimum solution for all parametric problems and beyond, and not only promises an optimum estimate, but also a simple all-purpose assessment of its accuracy. And all this comes with no need for the specification of a priori probabilities, and no complicated derivation of distributions. Furthermore, it is capable of being automated in modern computers and extended to any number of dimensions.

At a superficial level, the idea of maximum likelihood must be prehistoric: early hunters and gatherers may not have used the words "method of maximum likelihood" to describe their choice of where and how to hunt and gather, but it is hard to believe they would have been surprised if their method had been described in those terms. It seems a simple, even unassailable idea: Who would rise to argue in favor of a method of minimum likelihood, or even mediocre likelihood? And yet the mathematical history of the topic shows this "simple idea" is really anything but simple, and it reveals unsuspected pitfalls that are still of relevance. Joseph Louis Lagrange, Johann Heinrich Lambert, Daniel Bernoulli, Leonard Euler, Pierre Simon Laplace, and Carl Friedrich Gauss are only some of those who explored the topic, not always in ways we would sanction today. In the 20th century Ronald A. Fisher played a particularly important role leading to the modern theory, but such rigor as that theory enjoys today is due to primarily to Abraham Wald. I will review some parts of that history from Lagrange to the 1950s, drawing attention to ancient difficulties that remain of concern.

Our laboratory has worked on pinch-off and coalescence in several unusual experimental fluid systems, including superfluid helium-4. The singularities produced during these events can usually be described by a self-similar form, where quantities such as pressure and velocity diverge and length scales shrink to zero with characteristic power-law exponents. These solutions are often universal in the sense that they do not depend on the initial conditions, but this is not always the case. In most of our experiments, conventional high-speed video is used to examine the pinch-off and coalescence of classical and superfluid liquid drops and gaseous bubbles. However, investigating the asymptotic regime can be difficult due to the finite resolution of the camera and the diffraction of light. To avoid this problem, we developed an electrical technique using drops of liquid mercury to monitor the diameter of the singular region to just a few nanometers. In addition, we have explored the effects of dimensionality on pinch-off and coalescence using thin, quasi-2D liquid lenses floating on water (like drops of oil in vegetable soup). These results have motivated us to investigate idealized 2D pinch-off using boundary-integral simulations. Our analysis shows that unlike axisymmetric drops, non-viscous 2D pinch-off is described by a self-similar solution of the second-kind, where the power-law exponent is a non-rational number. We calculate this number independently solving a nonlinear eigenvalue problem. Another type of singularity in classical fluid flow is the motion of a liquid/solid/gas contact-line (e.g. droplet sliding on a plate). We are currently exploring this problem using superfluid droplets on cesium surfaces. Results and future work will be discussed.

Topological quantum computation is a new, emerging paradigm for a fault-tolerant quantum computation. The proposed topological quantum computer relies on the existence of non-Abelian anyons, which are quasiparticle excitations that display non-Abelian braiding statistics. Among various prospective candidates, certain fractional quantum Hall states are thought to possess the non-Abelian anyons suitable for topological quantum computation. In this talk, I will talk about (a) the intellectual motivation for topological quantum computation, (b) how Fibonacci anyons may be used for topological quantum computation, and (c) our recent experimental effort toward detection of the non-Abelian braiding statistics.

In our recent experiments, a light pulse is stopped and extinguished in one part of space and then revived and sent back on its way at a different location. In the process, the light pulse is slowed to 15 miles per hour and is also spatially compressed from 1 kilometer to only 20 microns. The light pulse is converted to matter, and a matter imitation of the light pulse travels between the two locations. At the revival position, the matter copy is converted back to light. Matter, as opposed to light, is easily manipulated, and changes induced in the matter copy are reflected in the revived optical pulse. The work demonstrates a powerful new method for coherent processing of optical information and has applications in optical computing and quantum information processing.

Molecular targeting is central to drug-based cancer therapy, but remains challenging because drugs often lack specificity, which may cause toxic side effects. I shall survey a translational bottom-up strategy to curb side effects by reassessing the bearing of physico-chemical laws on the molecular phenotype.

Modulating side effects is difficult because targets within superfamilies are evolutionarily and hence structurally related. I shall focus primarily on kinases, the quintessential signal transducers and also important cancer targets. The lack of specificity of the anticancer drug imatinib enables it to be used to treat chronic myeloid leukemia, where its target is the Bcr-Abl kinase, as well as a portion of gastrointestinal stromal tumors (GISTs), where its target is the C-Kit kinase. However, imatinib also has cardiotoxic effects traceable to its impact on the C-Abl kinase. Motivated by this finding, we created a modified version of imatinib that hampers Bcr-Abl inhibition, re-focuses the impact on the C-Kit kinase and promotes inhibition of an additional target, JNK, required to reinforce prevention of cardiotoxicity. We established the molecular blueprint for target discrimination in vitro using spectrophotometric and colorimetric assays and through a phage displayed kinase screening library. We demonstrated controlled inhibitory impact on C-Kit kinase in human cell lines, and established the therapeutic impact of the engineered compound in a novel GIST mouse model, revealing a marked reduction of cardiotoxicity. These findings identify the re-engineered imatinib as an agent to treat GISTs with curbed side effects. The result probably reflects the first bottom-up translational approach to redesign a drug to curb its side effects.

Prior to the mid-1970s, optimization research centered on effective search within irregular, sometimes nonlinear attractor basins with a single minimum. Conjugate gradient methods, for example, were developed in that framework. The study of spin glasses and Monte Carlo simulation brought a realization that most interesting problems have multiple minima, and most engineering applications are satisfied with any minimum that satisfies certain objectives. A second contribution was the realization that phase transitions in disordered systems have consequences for the cost of search in typical (but not worst-case) conditions. Recent methods, such as message-passing solutions to cavity mean-field descriptions of combinatoric problems have brought at least a thousand-fold increase in the size of typically hard problems which are now numerically tractable. But now such methods are being used as Shannon-optimal decoders, in a situation in which only one solution, the correct decoding, is of interest. Provably correct methods such as linear and semidefinite programming may also apply. We have been studying combinatoric problems lying right at the boundary between convex and harder optimization, such as Sudoku.

How do we make hard decisions? A decision is a deliberation process that involves accumulation of evidence for possible alternatives, ultimately leading to the commitment to a categorical choice. Recent physiological studies with behaving nonhuman primates have begun to uncover neural signals at the single-cell level that are correlated with specific aspects of subject's decision computations. In this talk, I will present a biophysically-based recurrent network model of spiking neurons for decision making. I will show that this model accounts for a range of observations from two sets of monkey 'experiments': one on perceptual decision making in a visual motion direction discrimination task, the other on internal valuation of competing alternatives and action selection in a foraging task. This model suggests a unified circuit mechanism for decision making, namely NMDA-receptor dependent slow neuronal reverberation that can be described theoretically in terms of stochastic attractor dynamical systems.

Models suggest that the earth and magnets crackle alike! Recent studies show that slowly increasing magnetic fields in magnets can trigger so-called "magnetizing avalanches". It turns out that we can model statistics of earthquakes, especially in irregularly shaped fault zones, very similarly, and this similarity motivates a new way of analyzing seismic data. I will show how we can understand the universal, i.e. detail independent, effects of disorder in both systems in terms of the theory of phase transitions.

Biocomplexity is the term that is becoming used to describe efforts to understand strongly-interacting dynamical systems with a biological, ecological or even social component. I provide a brief overview of why this field is not only interesting for physicists, but can benefit substantially from their participation. In particular, microbes represent a fascinating opportunity for physicists to contribute to biology, because their strong interactions, via both signalling and exchange of genes, means that the techniques of statistical mechanics are ideally suited to exploring the ecology of microbial communities and even the evolutionary dynamics of microbial genomes.

I describe our work at Yellowstone's Mammoth Hot Springs, to answer the following questions: do heat-loving microbes play a role in the dynamics of landscape evolution? And how can we quantitatively account for the architecture of the landscape in the vicinity of geothermal hot springs?

Sponsors of Nigel Goldenfield's talks include the JFI, the CI, the IBD, and the CIS lecture series.

Can we use computational algorithms to make accurate predictions of physical phenomena? In this talk, intended for non-experts, I will give examples where complicated space-time phenomena can be exquisitely captured with simple computational algorithms, that not only produce patterns resembling those seen in experiment, but also make accurate predictions about probes of dynamics and spatial organisation, such as correlation functions. In the last part of this talk, I describe how to handle materials pattern formation when structure emerges on multiple length and time scales, from atoms to polycrystalline sample dimensions.

Sponsors of Nigel Goldenfield's talks include the JFI, the CI, the IBD, and the CIS lecture series.

Relics of early life, preceding even the last universal common ancestor of all life on Earth, are present in the structure of the modern day canonical genetic code. In this talk, I will draw attention to these relics, and discuss their interpretation from the perspective of the dynamical system that is evolution. I will argue that this viewpoint, and the quantitative, statistical dynamical calculations that it entails, suggest a natural scenario in which evolution exhibits three distinct dynamical regimes, differentiated respectively by the way in which information flow, genetic novelty and complexity emerge. Possible observational signatures of these predictions are discussed.

Sponsors of Nigel Goldenfield's talks include the JFI, the CI, the IBD, and the CIS lecture series.

Just over one-hundred years ago Prandtl introduced the new concept of "boundary layers" to explain, analyze and model fluid flow behavior near surfaces. Today we can use similar ideas for interfaces where rapid local changes occur in fields including economics, political and social systems, biomedical applications, and even psychology. Since modeling the rapid changes in this boundary layer generally requires more detailed physics than in the slowly varying "outer" regions, special mathematical tools, i.e., singular perturbation analysis, had to be developed to connect the different regions. For example, the method of matched asymptotics has contributed a great deal to our understanding of turbulent boundary layers, starting with the classical two-layer approach of Millikan, which leads to the logarithmic velocity profile in the overlap region between "inner or small scales" and "outer or large scales," and the "von Karman constant". Nearly all currently used commercial codes for computation of flow in applications including aeronautics, energy generating machines and weather prediction rely on such a Karman constant. However, our recent examination of boundary layers with streamwise pressure gradient, and pipe and channel flows indicates that the von Karman coefficient of the log law is not universal, and exhibits dependence on not only the pressure gradient but also the wall-bounded flow geometry, thereby raising fundamental questions regarding turbulence flow theory and modeling for all wall-bounded flows.

When a cells crawls, its shape re-organizes via polymerization and depolymerization of a network of actin filaments. The growing ends of the filaments are localized near the outside of the cell, and their polymerization, regulated by a host of proteins, pushes the cell membrane forwards in a biological model known as the dendritic nucleation model. The same dendritic nucleation mechanism comes into play when the bacterial pathogen Listeria monocytogenes infects a cell. The bacterium hijacks the host cell's actin machinery to create an actin network (the actin comet tail) that propels the bacterium through cells and into neighboring cells. I will discuss recent results from Brownian dynamics simulations that suggest a new picture for the physical mechanism underlying this form of motility.

Aqueous interfaces are ubiquitous and play a fundamental role in biology, chemistry, and geology. The structure of water near interfaces is of the utmost importance, including chemical reactivity and macromolecular function. Theoretical work by Chandler et al. on polar-apolar interfaces predicts that a water depletion layer exists between a hydrophobic surface and bulk water for hydrophobes larger than ~20nm^2 (a ~4A in radius apolar molecule). Until now, what the interface really looks like remains in dispute since recent experiments give conflicting results: from complete wetting (no water depletion layer) to a water depletion layer. Those experiments that have found a water depletion layer report 40-70% water in the depletion zone: 40-70% and a width of ~3A. However, an alternative interpretation to the profiles exists where no depletion layer is required. By studying hydrophobic self assembling monolayer surfaces against several water mixtures of D2O and H2O we obtained the hydrophobic/water profile by phase sensitive neutron reflectivity. With this model independent technique we observe a 2 times wider and drier depletion water layer: 6A thick and 0-25% water. Given the level of disagreement, I will review and discuss the topic of immiscible interfaces.

It is clear that evolution tends to optimize fitness if it can. The question for research is what are the constraints under which this optimization is done. A theory of biological design thus must include mathematical formulations of these constraints. This talk will present experimental data that measures the fitness as a function of molecular parameters in E. coli, and laboratory evolution epxeriments that follow the optimization process directly. This is used to suggest the beginnings of a theory for understanding basic design questions: What sets the concentration of as protein in the cell to a specific value? What is the cost and benefit of a regulatory interaction? What is the cost of stochastic noise in the design? The blackboard will be used to hopefully invite audience interaction.

[E. Dekel and U. Alon, Optimality and evolutionary tuning of the expression level of a protein. Nature, 436, 7050, 588-922 (2005).],

Sponsors of Uri Alon's talks include the MRSEC, the IBD, the CI, and the CIS lecture series.

Biological networks of interactions are of course very complex. Recently, however, some biological networks, namely those that control gene expression, have been found to display a degree of simplicity: they seem to be built of only a small set of recurring inetraction patterns. These elementary patterns, called network motifs, can each carry out a specific dynamical function in the network. These functions have been studied experimentally using high resolution experiments in living cells. The same network motifs seem to be found across organisms from bacteria to humans. Network motifs are found also in other types of biological networks, including neuronal networks. This raises the hope that the dynamic of complex biological entworks could be understood in terms of elementary circuit patterns.

[Uri Alon, Network motifs: theory and experimental approaches. Nature Reviews Genetics 8, 450-461 (2007).],

Sponsors of Uri Alon's talks include the MRSEC, the IBD, the CI, and the CIS lecture series.

Bats, whales, and cows all evolved from an ancestral mammal in less than 100 million generations. In contrast, computer simulations of evolution need far more generations to solve rather simple computational problems. There may thus be a challenge to understand the speed of natural evolution. This talk will present a computational study of evolution that demonstrates ways to dramatically speed evolution, based on temporally varying goals. It is seen how speedup of evolution is linked with spontaneous emergence of modular structure in the organism.

[N. Kashtan, E. Noor and U. Alon, Varying environments can speed up evolution. PNAS, 104: 13711-13716 (2007).],

Sponsors of Uri Alon's talks include the MRSEC, the IBD, the CI, and the CIS lecture series.

Despite the buildup, completing the sequencing of the genome was at best anticlimactic, and the functions of most of the genes remain mysterious to this day. Hopes for systems biology to explain how the genome works rest on the hypothesis that comprehensive and quantitative measurements of gene activities will reveal the fundamental mechanisms that determine cell growth, metabolism, interactions and identity. To date, systems biology's greatest successes have been in understanding gene expression, where comprehensive analysis has become straightforward in the last ten years. The RNAs that derive from transcription of each gene can be reliably isolated from the organism and then individually measured using highly multiplexed tools such as hybridization microarrays. Sophisticated informatics permits the investigator to compare many conditions and recognize patterns of gene activity that correspond to distinct cell states, revealing the logic of the cell.

This happy story is in stark contrast to the state-of-the-art in comprehensive analysis of cellular proteins. Proteins are considerably more diverse than RNA and there seems no future for a generic protein detection technology equivalent to the DNA microarray. Despite a decade of pundits touting mass spectrometry as the enabling technology for analysis of cellular proteins, current tools and methods do not offer the sensitivity, dynamic range or throughput required and there seems no clear path to comprehensive analysis. Our group of experimentalists and informaticists has been working to reinvent mass spectrometry proteomics with high throughput comprehensive analysis in mind. We will present the current state of mass spectrometry experiments and informatics, exploring strengths and weaknesses, and describe an alternative approach that can overcome many of the current limitations. We are developing experimental and computational strategies, hoping to take full advantage of the capabilities of current and future mass spectrometers to identify and measure proteins. Successful implementation would have the potential for significant impact on medicine and industry and provide one of the missing tools for systems biology.

An important characteristic of flocks of birds, schools of fish, and many similar assemblies of self-propelled particles is the emergence of states of collective order in which the particles move in the same direction. When noise is added into the system, the onset of such collective order occurs through a dynamical phase transition controlled by the noise intensity. While originally thought to be continuous, the phase transition has been claimed to be discontinuous on the basis of recently reported numerical evidence. This has originated a (heated) debate about the nature of the phase transition, i.e. whether it is continuous or discontinuous. In this talk I will present evidence showing that the phase transition actually depends crucially on the way in which the noise is introduced into the system. Such a dependence was not taken into account in previous studies of swarms and flocks, which is probably what caused all the confusion about the onset of collective order in these systems.

Recent experiments show that when an air bubble breaks away from an underwater nozzle, the thin neck that pinches off retains a detailed memory of initial asymmetries in its shape (Keim et al, Phys. Rev. Lett. 97, 144503 (2006)). This is in contrast to other break-up studies (e.g. water falling from a faucet) which reveal universal break-up dynamics. Motivated by these observations, we consider the singularity dynamics of a collapsing 2-D circular hole in water. Upon perturbing the natural circular symmetry, memory is manifested as the conservation of the size of the initial distortion and in vibrations of the shape as the hole closes. As break-up is approached, the vibrations dramatically alter the final stages of the singularity. We show that this ideal implosion is relevant to reality by directly comparing the 2-D model to vibrations induced in experiments by the release of a bubble from a slot-shaped nozzle.

Ion channels are proteins with a hole down their middle that act as the "valves of life". Ion channels control the flow of ions (hard spheres) like Na+ , Ca2+ , K+ , and Cl- across the otherwise insulating membrane of cells. They act much like Field Effect Transistors which control the flow of quasi-particles - holes and electrons - through glass "membranes" (layers).

Channels open and close suddenly ("gate") and different channels control this opening and closing in very different ways. The control and mechanism of gating is studied by hundreds if not thousands of scientists every day because of the clinical and biological importance of these valves of life. If the valves of a car, or your plumbing, get stuck, everything goes wrong. If a transistor sticks open, the computer stops. If a channels sticks open, the patient dies of hyperthermia (for real!).

The mechanism of opening and closing of channels is not known. Here we propose that an empty space - a bubble - is the gate that opens and closes channels. When the empty space fills with ions (and water), current flows and the channel conducts. Ions cannot cross the empty space and so a channel containing a bubble has a closed gate. It cannot conduct current.

Gaseous anesthetics - including xenon - are known to interfere with gating even though they do not bind to receptors and do not fit in the usual receptor paradigm of pharmacology. We propose that xenon acts by modifying and filling bubbles.

Periodic elastomeric cellular solids are subjected to uniaxial compression, and novel transformations of the patterned structures are found upon reaching a critical value of applied load. The results of a numerical investigation reveal that the pattern switch is triggered by a reversible elastic instability. Excellent quantitative agreement between numerical and experimental results is found and the transformations are found to be remarkably uniform across the samples. Moreover the phenomenon is found to be robust for a range of soft solids including rubber and jelly. Potential applications in phononic and photonic crystals will be discussed.

The puzzle of why fluid motion along a pipe is observed to become turbulent as the flow rate is increased remains the outstanding challenge of hydrodynamic stability theory, despite more than a century of research. The issue is both of deep scientific and engineering interest since most pipe flows are turbulent in practice even at modest flow rates. All theoretical work indicates that the flow is linearly stable i.e. infinitesimal disturbances decay as they propagate along the pipe and the flow will remain laminar. Finite amplitude perturbations are responsible for triggering turbulence and these become more important as the non-dimensionalized flow rate, the Reynolds number Re, increases. Our experimental work has shown that the threshold amplitude scales with Re and this gives new insights into origins of the turbulent motion through connections with recent theoretical and numerical results.

The flow of granular media on a rough surface has many realizations in nature, from rock slides and avalanches to dense ash flow during volcanic eruptions. I will describe laboratory experiments where precise measurements of such flows can be made with controllable parameters such as inclination angle, volume flow rate, and grain size, shape and composition. I will present a phase diagram of accessible states, from avalanches to uniform flowing states which can be unstable to the formation of lateral patterns, and finally a "liquid-gas" transition from a well defined layer to an "evaporated" low density state. Of particular interest are intermittent avalanches where the size and speed of spatially localized avalanches depend qualitatively and quantitatively on grain size and shape: smooth grains lead to stable shock-like solutions whereas rough grains lead to breaking, overturning fronts.

The brief history of rain theories, from primordial chaos to modern turbulence, will be presented. Recent experimental and theoretical results on fractal distribution of water droplets in clouds will be reviewed. Some unsolved problems of cloud physics will be described along with their relations to problems in field theory and condensed matter physics.

The complex, highly reproducible shapes of epithelial cells in the Drosophila eye are crucially dependent on the expression of adhesion molecules (cadherins). We show that not only the overall tissue organization, but the shape of each individual cell can be understood through quantitative modeling using minimization of an interfacial energy functional. The model contains only two free parameters, encoding for the adhesion strengths of E- and N-cadherin, and reproduces interfacial angles and lengths to within a few percent accuracy. Characteristic morphological changes in mutant ommatidia can be modeled within this approach, indicating an important role of changing levels of cadherin expression during morphogenesis.

This talk will deal with the response of pine cones to humidity fluctuations. The scales of the cones are known to close on rainy days, they bend and open up when they dry. This mechanism enables the cones to release seeds and the trees to reproduce. We are interested in understanding the dynamics of these processes. The structure of the pine cone scale may be reproduced in very simple devices. I will show some potential applications of these cheap biomimetic systems.

Hydrophobic surfaces can be made superhydrophobic by creating a texture on them. This effect, sometimes referred to as the "lotus effect", is due to air trapping in the structure, which provides a composite surface made of solid and air on which the deposited drop sits.

We will present recent experiments done on such superhydrophobic surfaces, made of forests of micro-pillars. We will see in particular what happens when water drops evaporate on such surfaces or when they impact them. We will also present experiments achieved on surfaces made of density gradient of micropillars, and will discuss the possibility of inducing spontaneous drop motions on such surfaces.

A last part of the talk will be devoted to imbibition phenomena. We will see that contrary to water drops, oil drops prefer to invade micro-textures or micro-channels with kinetics which depend on the local geometry.

The basics of glass science (structure, formation, thermodynamic stability, relaxation and atomic transport) as they apply to metallic alloys are reviewed. The essential phenomenology of mechanical behavior is presented: stiffness, homogeneous deformation (creep), inhomogeneous deformation (shear bands), and fracture (ductile and brittle). All of these phenomena can be understood based on ordering and disordering processes on the atomic scale. Experiments on colloidal glasses allow a direct look at the atomic scale mechanisms.

A Brownian sieve is a microstructured device that combines the effects of thermal noise, spatial asymmetry, and external forces to separate particles based on their transport properties. The separation characteristics of these systems can be modelled in terms of the motion of Brownian particles on a 2-D periodic potential. By treating the motion of an individual particle as a cyclical process in which the particle fluctuates away from, and then returns to the origin of any unit cell of the periodic potential we derive expressions for the averages and all moments for the number of periodic displacements in the horizontal and vertical directions in each excursion. The average displacements in the x- and y-direction obey symmetry relations for arbitrary values of the external forces, extended reciprocal relations through second order are shown to hold. Using the Onsager-Machlup thermodynamic action theory for the probabilities new symmetry relations for particle trajectories in the presence of magnetic fields. The magnetic effects are very small for colloidal particles in solution but may be significant in other contexts such as electron and spin transport on patterned superconductors.

I will briefly review the phenomenology of the glass transition, stressing those issues that are confused in the literature and confusing the interested community. I will present rigorous results regarding some popular models of the glass transition, showing that the common beliefs that glasses lose ergodicity and are "jammed" in some sense are not true. Having ergodicity resurrected, we apply statistical mechanics to shed some new light on the phenomena of interest.

The simplest models of matter posit a linear relationship between the stress and deformation, as for example in Hooke's law. However, many useful and important fluids (such as shampoos, industrial slurries, geophysical fluids, polymeric melts) exhibit a nonlinear response to stress. I will discuss the behavior of shear thickening fluids subjected to vertical vibrations in the context of pattern forming systems. I will show that a mixture of cornstarch/water or glass beads/water vibrated above a critical acceleration (approximately 10 g) is unstable to perturbations. At low accelerations a small indentation of the fluid surface will grow until it reaches the bottom of the container, forming a circular hole. At higher accelerations the rim of the hole becomes unstable and develops an upward growing tongue. At even higher accelerations, the entire layer writhes in a disordered manner. The mechanism for these instabilities is unknown. I will present experimental correlations between these instabilities and the fluid's rheological proprieties and attempts to model this phenomenon.

The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this talk I investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. By analyzing hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implementing these data into the Boolean models of the genetic networks, I will show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us.

The boundary of the basin of attraction of the stable 'laminar' point is investigated for several of the dynamical systems modeling subcritical instability. In the cases thus far considered, this boundary contains a linearly unstable structure (equilibrium point or periodic orbit). The stable manifold of this unstable structure coincides at least locally with the basin boundary. The unstable structure plays a decisive role in mediating the transition in that transition orbits cluster tightly around its (one-dimensional) unstable manifold, illustrating a scenario proposed by Waleffe. The picture that emerges augments the bypass scenario for transition and reconciles it with Waleffe's scenario.

We consider a model proposed by Waleffe (W97) for which an unstable equilibrium point U lies on the boundary. We find numerically that all orbits staring near U decay toward the origin, whereas 'half' of them should remain permanently bounded away from the origin. We offer an interpretation of this tendency toward decay based on the structure of the basin boundary.

When subjected to strong electric fields, raindrops in thunderclouds, pendant drops in electrospray mass spectrometry, and planar films form conical tips and emit thin jets from their tips. Theoretical analysis of the temporal development of such electrohydrodynamic (EHD) tip-streaming or cone-jetting phenomena has heretofore been elusive given the large disparity in length scales between the macroscopic drops/films and the microscopic jets. Here, simulation and experiment are used to investigate EHD tip-streaming from a liquid film of finite conductivity. In the simulations, the full Taylor-Melcher leaky-dielectric model, which accounts for charge relaxation, is solved to probe the mechanisms of "Taylor" cone formation, jet emission, and breakup of the jet into small drops. Simulations show that tip-streaming does not occur if the liquid is perfectly conducting or perfectly insulating. A scaling law for sizes of micro-(nano-)scale drops produced from the breakup of the thin jets is also developed. The reported advances have implications to a variety of new application areas ranging from microfluidics to printing of flexible electronic circuits.

Dynamics of vesicles in external flows has been a subject of great experimental and theoretical attention recently. A vesicle can exhibit a variety of different dynamical behaviors when placed in an external flow. At least three qualitative different motions have been observed in recent experiments: tumbling, tank-treading, trembling. I will review these experiments and will present a theoretical analysis of this effect, resulting in a phase-diagram which predicts the type of the vesicle motion. For planar external flows, the character of the vesicle dynamics is determined by two dimensionless parameters, which are formed out of viscosities of inner and outer fluids, external velocity gradient matrix and vesicle excess area. Transitions between different types of motions are analyzed separately. The tank-treading to tumbling transition is described by a saddle-node bifurcation whereas the tank-treading to trembling transition occurs via a Hopf bifurcation. In the vicinity of the transition lines the vesicle experiences critical slowing down, which can be described universal scaling exponents. In the end of the talk I will also discuss the effect of vesicle wrinkling in extensional flows.

Texas, like all other states, has been gathering test data on public school students for many years. What can one do with test records from 4 million students? I have been visualizing math test scores using ideas loosely borrowed from statistical mechanics and fluid mechanics. The visual representations give a more complete picture than is obtained by focusing on single numbers. They make it possible to address questions about the relative importance of income levels, race, and other factors in the Texas public K-12 educational system, and about whether testing pressure is improving educational performance. I will also comment on local, state, and national efforts in which I have been involved to better educate science and mathematics teachers.

Several current approaches to quantum gravity construct or derive models of quantum spacetime as discrete quantum systems on dynamical lattices. The key problem to be resolved in these models is whether and how classical spacetime arises from a discrete quantum system. This problem of the emergence of spacetime in the low energy limit is thus a problem in critical phenomena. I will introduce some of the models of quantum spacetime of current interest and illustrate the progress being made using them towards the problem of the emergence of classical spacetime. I will emphasize an important question, which is currently the subject of experimental probes, which is the symmetry of the ground state: is it Poincare, broken Poincare or quantum deformed Poincare?

There comes a time in each of our lives where we grab a thick section of the morning paper, roll it up and set off to do battle with one of nature's most accomplished aviators - the fly. If however, instead of swatting we could magnify our view and experience the world in slow motion we would be privy to a world-class ballet full of graceful figure-eight wing strokes, effortless pirouettes, and astonishing acrobatics. After watching such a magnificent display, who among us could destroy this virtuoso? How do flies produce acrobatic maneuvers with such precision? Are they flying in the most efficient way possible? What control mechanisms do they need to maneuver? More abstractly, what problem are they solving as they fly? Despite pioneering studies of flight control in tethered insects, robotic wing experiments, and fluid dynamics simulations that have revealed basic mechanisms for unsteady force generation during steady flight, the answers to these questions remain elusive. In this talk I will discuss our strategy for investigating these unanswered questions. I will begin by describing our automated apparatus for recording the free flight of fruit flies and a new technique called Hull Reconstruction Motion Tracking (HRMT) for backing out the wing and body kinematics. I will then show that these techniques can reveal the underlying mechanisms for dodge and strafe flight maneuvers that require lateral force generation. Finally I will describe a new approach for exploring the flight stability and control system of these insects.

We use optical tweezers to manipulate single DNA molecules, enabling a wide array of different studies in polymer physics and molecular biology. Here we review several recent projects. In one application, we directly measure the forces confining a single entangled DNA molecule. We directly confirm and quantify for the first time the precise nature of the "tube" constraint postulated in the reptation model of P.G. de Gennes. In another application, relevant to biochemical regulation, we study protein-mediated DNA looping and show that loop size and unbinding force distributions are highly variable and do not depend solely on the mechanical properties of DNA. In another application, we study the packaging of DNA into viruses. We show that this process is driven by a very strong ATP-powered molecular motor that must exert large forces to overcome large forces that resist the dense DNA confinement inside viruses. We show that electrostatic repulsion and ionic screening are major factors governing the resistance forces. We are now investigating the mechanism of three different viral DNA packaging motors using biophysical, biochemical, and genetic methods. Finally, we recently became interested in studying why and how long strings tend to become knotted (DNA molecules, iPod headphone cables, umbilical cords, etc.). We have made some progress towards answering this question by applying concepts from mathematical knot theory.

Matrices are used to describe the modes of oscillation of physical objects. Generally, N by N matrices describe objects with N modes. Often, when the objects are composed of pieces arrayed in a line, the matrix elements depend only upon the relative position along the line. They are then called Toeplitz matrices. We calculate the eigenvectors of large matrices of this kind by making use of calculations for infinite matrices. Propagation of information over the whole range of spatial indices in these eigenvectors is demonstrated by power law and logarithmic N-dependence of the eigenvalues and eigenvectors. The dependences can be interpreted in terms of the transfer of information along the line of objects described by the matrix.

Hui Dai, Zachary Geary, and Leo Kadanoff

Self-assembly of chemically-synthesized colloidal nanocrystals can yield complex long-range ordered structures. Nanocrystals of different size and functionality (noble metals, semiconductors, oxides, magnetic alloys) can be induced to self-assemble into ordered superlattices. We have built a variety of binary superlattices from monodisperse nanocrystals, mixing and matching these nanoscale building blocks to yield multicomponent assemblies. We have identified superlattices with cubic, hexagonal, tetragonal, and orthorhombic symmetries, isostructural with NaCl, CuAu, AlB2, MgZn2, MgNi2, Cu3Au, Fe4C, CaCu5, CaB6 and NaZn13 compounds emphasizing the parallels between nanoparticle assembly and atomic scale crystal growth. We even demonstrated the formation of nanoparticle superlattices with dodecahedral quasicrystalline ordering.

What brings spherical nanoparticles together and packs them into these sophisticated low-symmetry superlattices? Observed structural diversity has shown that we have very limited understanding of the processes and interactions that govern self-assembly of nanoscale objects, formation of complex structures and their thermodynamic stability. I will discuss the delicate balance of competing inter-nanoparticle interactions that can be responsible for formation of binary nanoparticle superlattices.

I will show that ordered nanocrystal assemblies can be used as model systems for studying transport phenomena in low-dimensional materials. The exchange coupling energy in the nanocrystal assemblies can be tuned by tailoring interparticle spacing; the conductivity of nanocrystal solids can be switched between n- and p-type transports by surface transfer doping. Doping of PbSe and PbTe nanocrystal solids can also occur through the exchange coupling with other semiconductor (Ag2Te) or metal (Au) nanocrystals in binary nanocrystal assemblies.

Molecular Dynamics and stochastic collision dynamics (DSMC) particle methods allow testing of the approximations in the Navier-Stokes approach to hydrodynamic flows. The neglect of correlations leads to divergence of transport coefficients in 2 dimensions and the Burnett coefficients in 3 dimensions. From shock simulations, the neglect of nonlinear effects seem relatively small. The use of boundary conditions with amplitude variations, instead of stick boundary conditions, removes the dilemma of no linear instability in pipe flow at any Reynolds number, as well as possibly explaining the drag reduction problem when a small amount of polymer is introduced in the fluid. The neglect of fluctuations in the Rayleigh-Taylor instability leads to an incorrect long time behavior, however, by adding fluctuations to the continuum equations, the correct behavior should be recovered.

The Rayleigh-Taylor instability was simulated in a comparable amount of computer time as the Navier-Stokes calculation for a comparable period of the mixing process, using about 1 billion particles,so as to avoid boundary effects. The short time behavior is shown to be quantitatively given by linear stability analyses, starting from a flat interface, roughened only by natural fluctuations. The merging of the mushrooms leads to a quadratic time dependence for the advance of the mixing front, with a coefficient in agreement with experiment. Subsequently, the front slows to a linear time dependence as drops break off from the stems of the mushrooms, and Stokes law applies. Magnetic levitation experiments confirm these results.

I will present an analytical theory that explains the experimentally-observed shapes of vesicles in AC electric fields [1]. The model treats the inner and suspending media as lossy dielectrics, and the membrane as an ion-impermeable flexible incompressible-fluid sheet. The vesicle shape is obtained by balancing electric, hydrodynamic, and bending stresses exerted on the membrane.

The theory predicts that stationary vesicle deformation depends on field frequency and conductivity conditions. If the inner fluid is more conducting than the suspending medium, the vesicle always adopts a prolate shape. In the opposite case, the vesicle undergoes a transition from a prolate to an oblate ellipsoid at a critical frequency, which the theory identifies with the inverse membrane charging time. At frequencies higher than the inverse Maxwell-Wagner polarization time, the electrohydrodynamic stresses become too small to alter the vesicle's quasi-spherical rest shape. The analysis shows that the evolution towards the stationary vesicle shapes strongly depends on membrane properties such as viscosity. The model can be used to rationalize the transient and steady deformation of biological cells in electric fields.

[1] Aranda et al. Biophys. J. 95 L19-21 (2008)

Capillary forces are responsible for a large range of everyday observations: the shape of rain droplets or the imbibition of a sponge. Although they are weak at macroscopic scale, surface capillary forces may overcome volume forces at small scales and deform compliant micro-structures. Capillary-induced sticking can indeed prevent the actuation of mobile elements in micro-electro-mechanical systems (MEMS), or even cause their collapse. I will present a few experimental situations where capillary forces are able to deform two types of elastic objects: rods, and thin sheets. How many hairs are present in a bundle of wet fur? Can a thin sheet spontaneously wrap around droplet? I will try to describe how these different experiments are connected to the same length scale.

The study of the elasticity of thin objects (sheets or rods) is a rapidly burgeoning field that is bringing together seemingly separate communities ranging from non-linear and statistical physics through to differential geometry and nanotechnology. Moreover, coupling the elasticity of thin objects with other phenomena - such as fracture, surface tension, and adhesion at a solid or liquid interface - represents a new fundamental challenge.

In this talk I shall explore, mostly through experiments, two problems that involve the elasticity of thin sheets adhered to solid interfaces: 1) Localization through surface folding in solid foams under compression and 2) Blistering of a thin sheet adhered to a soft elastic substrate.

What is the dynamics of drying in porous media? It has been difficult to visualize due to the non-transparency of the media. We study this phenomenon in an optical index matched system with confocal microscopy. We observe abrupt air invasions which result from the strong flow from menisci in large pores to menisci in small pores. The size and structure of the air invasions are in accord with 3D invasion percolation. By varying the particle size and contact angle we unambiguously demonstrate that capillary pressure dominates the drying process.

Bubble nucleation at surfaces is a poorly understood phenomenon. We did visualization experiments at hydrophobic surfaces structured at the microscale and compared the results with both boundary integral simulations and Rayleigh-Plesset type model calculations, in particular focusing on bubble-bubble interactions. It is demonstrated that in the many bubble case the bubble collapse is delayed due to shielding effects. We succeed in making cavitation totally reproducible in space and time. When reducing the surface structure by a factor of 10 to about 100nm, one reaches the scale of the so-called surface nanobubbles. These are structure seen in atomic force (AFM) microscopy images. We will give evidence that these structure are indeed bubbles and will analyse the conditions under which they form. However, we find them to be stable against massive pressure 'reduction': Surprisingly, their appearance is uncorrelated with bubble nucleation events on the surface.

Surface nanobubbles do not act as bubble nuclei, Bram Borkent, Stephan Dammer, Holger Schoenherr, Julius Vancso, and Detlef Lohse, Phys. Rev. Lett. 98, 204502 (2007).

Controlled multi-bubble surface cavitation, Nicolas Bremond, Manish Arora, Claus-Dieter Ohl, and Detlef Lohse, Phys. Rev. Lett. 96, 224501 (2006).

Colloidal suspensions are excelent model systems for a variety of complex fluids, and moreover are ubiquitous in industrial and technological applications. In particular, the flow properties of attractive colloidal suspensions determine their utility as inks, paints, coatings, and personal care products. We investigate the flow properties of colloidal gels in microchannels and constrictions using confocal microscopy and finite-element modeling. Under shear flow, the suspension contains dense clusters that yield at intercluster boundaries, resulting in network breakup at high shear rates. These structural changes coincide with a transition from pluglike flow at low pressures to fluidlike flow at high pressures.

The foremost observable property of turbulent flows is their spatial and temporal unsteady structure - a scale-free pattern of motions originating from the conservation of momentum and the degree of compressibility of the fluid. However, previous attempts at explaining certain macroscopic properties of these flows ignore their rich structure in favor of treating only the average behavior. I will talk about how the friction drag in a rough pipe and the wall velocity profile depend on the spectrum of turbulence. The roughness and finite Reynolds number act as thermodynamic variables on the approach to a dynamical critical point, as evidenced by an observed data collapse. I test this proposition with direct numerical simulations of 2D turbulence, in which (unlike in 3D flows) the spectrum of fully developed turbulence depends on how it was initiated. I will also present the numerical method used for the simulation, which uses conformal mapping to capture the geometry of the rough pipe walls.

For the nervous system to work at all, a delicate balance of excitation and inhibition must be achieved; too much excitation, and the brain becomes "epileptic"; too little excitation and it goes "flatline". However, when such a balance is sought by global strategies, only few modes remain balanced close to instability, and all other modes are strongly stable. Here we present a simple model of neural tissue in which this balance is sought locally by neurons following `anti-Hebbian' behavior, namely, the strength of synaptic connections between neurons is decreased whenever the activities of the two neurons are correlated. Under this dynamics all degrees of freedom achieve a close balance of excitation and inhibition and the system becomes become "critical" in the dynamical sense, i.e., it has an extensive number of marginal degrees of freedom. At long timescales, the modes of our model oscillate around the instability line, so an extremely complex "breakout" dynamics ensues in which different modes of the system oscillate between prominence and extinction. We show the system develops various anomalous statistical behaviours and hence becomes self-organized critical in the statistical sense.

The ability of adherent cells to regulate traction forces on their extracellular matrix (ECM) is fundamental to tissue morphogenesis and directed cell migration. To a large degree, cellular traction forces are regulated by myosin-II generated cell contractility, which promotes the development of contractile F-actin bundles, the growth of mechanosensitive focal adhesions and large traction stresses exerted on the ECM. In the presence of the myosin-II ATPase inhibitor, blebbistatin, F-actin bundles dissociate, focal adhesions disassemble and traction stress exerted on the ECM is diminished. To address how myosin-II ATPase activity drives the organization of the F-actin cytoskeleton into structures capable of efficient force transmission, we utilized a combination of high resolution confocal microscopy and traction force microscopy. We found that myosin-II-mediated contractility induced an exponential recovery in traction forces with a half time of approximately 1.5 minutes. The force recovery correlated with rapid lengthening of focal adhesions and their associated stress fibers, but was inversely proportional to retrograde F-actin flow speed, which decreased from 4.5 to 0.25 um/min. These relationships indicate that, as focal adhesions assemble, F-actin rapidly reorganizes into compact bundles at timescales consistent with increase in force at adhesion sites. Once focal adhesions and F-actin bundles reached 2-3 and 3-5 um in length, respectively, changes in F-actin flow and traction forces occurred at much slower rates. We propose that enzymatic activity of myosin II promotes rapid reorganization of the F-actin cytoskeleton until myosin-II mediated tensile stresses within the cytoskeleton are balanced with traction stresses exerted on the ECM.

Many systems of significant fundamental and applied interest are microscopically irreversible. For theoretical studies of such systems, the steady-state distribution is of central importance because it enables calculation of static averages of observables for comparison to experimental measurements. For systems at equilibrium, low probability states can be explored efficiently in simulations with umbrella sampling methods, in which biasing potentials that are functions of one or more order parameters are used to enhance sampling of selected regions of phase space. What complicates extending umbrella sampling to simulations of non-equilibrium processes is that, by definition, they do not obey detailed balance (microscopic reversibility). As such, one must account for the fact that the steady-state probability of observing particular values of the order parameters can be determined by a balance of flows in phase space through different possible transitions. In this talk, I will describe an algorithm for enforcing equal sampling of different regions of phase space in an ergodic system arbitrarily far from equilibrium, which enables its steady-state probability distribution to be determined with high accuracy. Applications and extensions of the method will be discussed.

The 28-29 February, 2008, break-up of a part of the Wilkins Ice Shelf, Antarctica, (see http://mrsec.uchicago.edu/Comp_in_Sci/macayeal.mov) exemplifies the now-familiar pattern of "explosive" ice-shelf break-up thought to be a consequence of environmental warming in the Antarctic Peninsula region. Key aspects of this "explosive pattern" to be explained by theories of ice-shelf dynamics include:

The abrupt, near simultaneous onset of iceberg calving across a large-scale stretch of ice front

High outward drift velocity (~0.3 m/s) of a leading "phalanx" of tabular icebergs that formerly comprised the seaward edge of the ice shelf prior to the break-up

Efficient "surface coverage" of the ocean surface between the intact ice shelf and the leading phalanx of tabular icebergs by small icebergs, capsized icebergs and dismembered tabular icebergs (small irregular pieces)

Extremely large gravitational potential energy conversion rates, e.g., up to 3 x 1010 W, by the "inverted submarine landslide" process over short periods of time (e.g., hours to days) in the absence of significant ice deformation

The apparent lack of proximal iceberg-calving triggers (e.g., strong atmospheric storms in the local environment) at the time of break-up onset

The capacity for enabling conditions (e.g., presence of melt-water induced "hydrostatic fracture") to make possible multiple break-up events (e.g., a second pulse of the Wilkins Ice Shelf break-up in late May, 2008) distributed through various seasons.

I examine the basic dynamic features of ice-shelf/ocean-wave interaction (including ice-shelf sources of ocean waves) that may explain the above aspects of the explosive ice-shelf disintegration process. Ice-shelf generated surface-gravity waves and flexural-gravity waves associated with initial calving at an arbitrary "seed location" produce stress perturbations capable of stimulating calving on the entire ice front. Waves generated by parting detachment rifts, iceberg capsize and break-up stimulate the "inverted submarine landslide" process, whereby ice shelf of thickness Hi is converted to a field of iceberg rubble of thickness Hf

Dendritic channel networks are a ubiquitous feature of Earth's topography. A half century of work has detailed their scale-invariant geometry. But relatively little is known about how such networks grow, especially in natural settings at geologic time scales.

This talk addresses the growth of a particularly simple class of channel networks: those which drain groundwater. We focus on a pristine field site in the Florida Panhandle, in which channels extending for kilometers have been incised vertically through tens of meters of ancient beach sands.

We first present new field observations showing how the flow of subsurface water interacts with the geometry of the network. We then show that the growth of groundwater-driven networks is described by two linear response laws. Remarkably, one of these growth laws is reversible, which allows us to reconstruct network history and estimate network age. A particularly striking feature of the Florida network is the existence of a characteristic length scale between channels. Our theory predicts how this length scale evolves, thereby linking network growth to geometric form.

Nacre, or mother-of-pearl, is a layered biomineral composite. It is widely studied because of its self-assembled, efficient and accurately ordered architecture, its toughness, and its fascinating and poorly understood formation mechanisms.

The aragonite crystal tablets in nacre orient so that their c-axes are aligned perpendicular to the layers. We will investigate this orientational ordering and argue that it is established dynamically, via regulation of the kinetics of crystal nucleation and growth. An analytically solvable model yields substantial insight into the ordering process.

We study the local power fluctuations in numerical simulations of stationary, homogeneous, isotropic turbulence in two and three dimensions with Gaussian forcing. Due to near Gaussianity of the one-point velocity distribution, the probability distribution (PDF) of local power is well modeled by the PDF of the product of two joint normally distributed variables. In appropriate units, this distribution is parameterized only by the mean dissipation rate. The large deviation function for the power PDF is calculated exactly and shown to satisfy a Fluctuation Relation (FR) with a rate constant that depends upon the mean dissipation rate. However, this FR is entirely statistical in origin. I will provide a comparison of this model not only with our numerical data but also with related experiments wherever possible. Time permitting, I will also discuss some directions we are keen to explore in future.

The research in my laboratory focuses on the sensory ethology of fruit flies, treating these tiny insects not simply as convenient laboratory models, but as real animals that have evolved a successful life history pattern. The goal of this work is to try to deconstruct the animal's behavior into a sequence of sensory-motor modules. My talk will focus on several visually-mediated components of behavior including take-off, navigation, predator avoidance, landing, and local exploration, as well as components of social behavior that ensue whenever two or more flies alight on the same piece of rotting fruit

Adding a certain amount of water to a pile of sand increases its mechanical stability dramatically, leading to a material stiff enough for sculpturing sand castles. This is due to the liquid bridges formed between adjacent particles which introduce cohesion into the system. In this talk, I will present our recent investigations on how the cohesive force influences dynamic behaviors of granular matter. First, I will demonstrate with liquid helium-4, a liquid with a surface tension only 1/200 that of pure water, that the increase of mechanical stability by wetting is prominent. With the increase of helium added, the system undergoes dry, asperity wetting and complete wetting regimes. Remarkable difference between superfluid and normal fluid wetting is found in the asperity wetting regime, which we attribute to the enhancement of liquid bridges by the superflow of unsaturated helium film.

Second, I will present the phase diagram of wet granular matter under vertical vibrations focusing on the coexistence(C) regime of fluid(F) and gas(G) phases. Scaling of F-C transition line, dynamics of 'gas bubbles', interfacial tension between F-G phase boundary will be discussed. We also demonstrate that S-F transition is a surface melting process utilizing ruby fluorescence. In addition, a newly built microwave radar setup for particle tracing in 3D will be introduced briefly.

Third, aggregation of two dimensional wet granular matter under shear flow will be discussed. In this experiment, particles floating on a viscous liquid are wetted by an oil film, which gives rise to a hysteretic and short ranged capillary force between neighboring particles. The balance between the capillary force and the viscous drag forces determines the average size of clusters. The cluster size distribution, scaling between average cluster size and shear rate, and fractal dimensions of the aggregates will be presented and compared with simulations.

Many natural structures are made of soft tissue that undergoes complicated continuous shape transformations as a result of the distribution of local /active/ deformation of its "elements". Currently, the ability to mimic this shaping mode in man made structures is poor.

I will present some results of our study of actively deforming thin sheets.

Theoretically, we have formulated an elastic theory for such bodies and derived from it an approximate 2D plate theory for plates with intrinsic non-Euclidean metric.

Experimentally, we use environmentally responsive gel sheets that adopt prescribed metrics upon induction by environmental conditions. With this system we study the shaping mechanism and energy scaling in different cases of imposed metrics.

Finally, we measure growth of wild types and mutants leaves, attempting to link between their local growth tensors and the different evolution of their global shape.

Naturally growing tissue as well as environmentally responsive material may form thin elastic structures which are neither plates nor shells, and need not have a stress free configuration.

In this lecture I will discuss the elastic theory of non-Euclidean bodies and derive from it a reduced model for describing thin non Euclidean plates valid for large displacements but small strains, and arbitrary intrinsic geometry. I will describe some of the mathematical properties of the reduced model, such as the buckling transition, the convergence to an isometric immersion in the zero-thickness limit, and the appearance of a boundary layer along the free boundary at small, yet finite thickness. Finally, I will discuss the relevance of the theoretical framework to biological systems, and review some surprising solutions for specific elastic non-Euclidean plates such as helical strips of no intrinsic chirality

Messenger RNAs are unstable intermediates in the process of gene expression, namely the synthesis of proteins in a way that reflect cellular conditions. In recent years it became evident that regulation of gene expression occurs not only by regulating synthesis of the messenger, but also by regulating its properties. Taking a quantitative approach we suggest a unifying view of RNA-mediated regulation, highlighting the effect of processes in and out of equilibrium.

Eukaryotic genomes are packaged into nucleosome particles, in which a short stretch of the genomic DNA (~150 base pairs, 50 nm) is tightly wrapped around a tiny (~35 nm radius) spool-shaped protein core. Consecutive nucleosomes are separated by short stretches of unwrapped DNA. Nucleosomes are remarkable from a physical perspective because, in each nucleosome, one persistence length of DNA -- a lengthscale of DNA inflexibility -- is wrapped in nearly two full turns around the protein spool. Nucleosomes are important in biology, because they strongly occlude their wrapped DNA, thus the detailed locations of nucleosomes along the genome strongly impacts the ability of DNA binding proteins to access particular binding sites.

We have discovered that genomes care where their nucleosomes are located, and that genomes manifest this care by encoding an additional layer of genetic information, superimposed (multiplexed) directly on top of other kinds of regulatory and coding information that were previously recognized. The physical basis of the nucleosome DNA sequences preferences lies in the sequence-dependent mechanics of DNA itself. We have developed two different approaches to read this nucleosome positioning code and predict the in vivo locations of nucleosomes. One approach utilizes a knowledge-based mesoscopic model for the sequence-dependent mechanics of DNA, from which we compute an effective elastic free energy cost for wrapping different DNA sequences into a nucleosome. The other approach develops a statistical profile of the nucleosome sequence preferences; we take the log of the likelihood assigned by this profile to a given DNA sequence as an apparent negative free energy for nucleosome formation. We then exactly solve the 1-dimensional equilibrium distribution problem for placing self-avoiding nucleosomes onto the free energy landscape. Our statistical model, trained on nucleosome DNAs isolated in a purified system in vitro reconstitution experiment, is strongly predictive of nucleosome occupancy patterns in living yeast, C. elegans and human cells. Our mechanics model explains key features of the real nucleosome DNA sequence preferences. Our findings suggest that genomes utilize the nucleosome positioning code to facilitate specific chromosome functions and to define the next higher level of chromosome structure itself.

We present high resolution x-ray diffraction measurements on antiferromagnetic Chromium, which is known to exhibit strong coupling phenomena despite the familiar weak-coupling density wave ground state. We directly measure the spin- and charge-density wave order parameters as the magnetism is suppressed with applied pressure using diamond anvil cell techniques at the Advanced Photon Source. In the low pressure regime, the BCS-like ground state is manifest in the decades-long exponential suppression of the order parameters, while at high pressure this weak-coupling behavior is cut off by a quantum phase transition. We identify quantum confinement as the physics driving the exponential suppression of the antiferromagnetic phase. We find that Cr is unique among stoichiometric itinerant magnets studied to date insofar as the quantum phase transition is continuous in nature, allowing experimental access to the naked quantum singularity where the competition between the destabilized density wave and more strongly coupled ground states is most intense. Our results inform the growing body of evidence that weak- and strong-coupling phenomena indeed coexist in many solid state systems, such as continuously tuneable charge density waves in manganites, unconventional superconductivity in spin density wave Bechgaard salts, and charge density wave characteristics of the checkerboard order in the high-TC cuprates.

In this talk I will discuss various projects in which we take inspiration from nature to advance technology. The key idea behind these bio-inspired design projects is the belief that, thanks to natural selection, if a structure exists in nature that performs a desired function, it is tough for engineers to dramatically improve upon the natural design. Yet, historically, the countless failures in biomimetics have been more notorious than its successes (e.g. airplanes with flapping wings). There are many reasons for these failures -- impractical energy requirements and complexity of controls, among others. To avoid these pitfalls, our biomimetic studies focus on simple biological systems (preferably organisms with primitive or, better yet, non-existant central nervous systems) in which the energy requirements are low and the biological solutions to challenging questions are grounded in mechanics rather than in neurological controls.

We have moved into an era when: Climate Change is accepted as real; also accepted is the fact that human activities are the major drivers for many of the changes. One of the major, if not the major, changes predicted for this century is the near disappearance of the Hindu Kush-Himalayan-Tibetan (HKHT) glaciers. The glaciers and snow packs in the HKHT region provide the head waters for most major river systems of S. E and SE Asia and thus are vital for the food and water security of the region. Recent studies employing unmanned aircraft and satellites are yielding new insights into how air pollution and greenhouse warming are contributing to the rapid retreat of these glaciers and snow packs.

Ground-state problems naturally arise in many fields, including physics, biology, materials science, and mathematics. A classical ground-state configuration of a system of interacting particles is one that minimizes the system potential energy. In the laboratory, for example, such states can be produced by slowly cooling a liquid to a temperature of absolute zero, and usually the ground states are crystal structures. However, our theoretical understanding of ground states is far from complete. For example, it is difficult to prove what are the ground states for realistic interactions. I discuss recent theoretical/computational methods that we have formulated to identify unusual crystal ground states as well as disordered ground states [1,2,3,4]. Although the latter possibility is counterintuitive, there is no fundamental reason why classical ground states cannot be aperiodic or disordered.

1) M. Rechtsman, F. H. Stillinger and S. Torquato, Synthetic Diamond and Wurtzite Structures Self-Assemble with Isotropic Pair Interactions , Physical Review E, vol. 75, 031403 (2007).

2) S. Torquato and F. H. Stillinger, "New Duality Relations for Classical Ground States," Physical Review Letters, vol. 100, 020602 (2008).

3) R. D. Batten, F. H. Stillinger and S. Torquato, "Classical Disordered Ground States: Super-Ideal Gases, and Stealth and Equi-Luminous Materials," Journal of Applied Physics, vol. 104, 033504, (2008).

4) S. Torquato and F. H. Stillinger, "New Conjectural Lower Bounds on the Optimal Density of Sphere Packings," Experimental Mathematics, vol. 15, 307 (2006).

,

Hinds 101, 1:30

Adam Sobel, Columbia University

The influence of condensate evaporation on water vapor and its stable isotopes in a global climate model

Hinds 101, 3:00

Victor C. Tsai, Harvard University

Turbulent Hydraulic Fracture Applied to Water Drainage from a Melting Greenland Ice Sheet

This talk reviews the changing conceptions of basic physics that the plasma-physics community put forward in postwar America. I give special attention to the tense relationship between fusion research and the more general study of plasmas in astrophysics, space science, and industry. Although fusion research often led to results that were regarded as basic plasma physics, its dominating influence tended to weaken other plasma work. I show that the conceptions of basic physics put forward by the plasma community were not highly regarded or easily understood by science administrators and the general physics community. This difficulty had at least two aspects. First, fusion research so dominated the public conversation about plasma physics that other work on basic properties and phenomena of plasmas did not gain significant attention. Second, none of the conceptions of basic plasma physics (fusion or otherwise) ever gained the prestige of what I call the Big Questions conception of basic physics, the best example of which is the reductionist program of high energy physics. In contrast to the particle physicist's conception of unity in physics, plasma physicists sought to describe the varied behavior of plasmas with the common theoretical machinery of statistical mechanics and to link plasma behaviors on different scales, in the laboratory and in space.

Extremely fast biological movements often inspire notions of "pinnacles of evolution". However, by taking a look at the basic underlying physics of these movements, an alternative perspective emerges. Could some of these phenomena emerge as by-products of another behavior? Do these "accidents" provide the substrate for evolutionary change? In this talk, I will present two remarkable phenomena -- jaw-jumping in ants and cavitation-generating snail-smashing in mantis shrimp -- and probe the roles of by-product and natural selection in the evolution of fast animal movements.

Cellular states are plastic, and even terminally differentiated cells can be reprogrammed to a pluripotent state (i.e., an embryonic stem cell-like state) by ectopic expression of a few transcription factors. These recent experimental results have raised the possibility of creating patient-specific stem cells for regenerative medicine without the need for embryonic material. One of many challenges that must be confronted to make this exciting possibility a reality is that reprogramming efficiencies are very low. An understanding of the mechanisms that make reprogramming rare, and even possible, can help design more efficient strategies for creating pluripotent cells. The development of such mechanistic principles will also shed light on how cellular identity is maintained and transformed - a basic unresolved issues in biology. I will describe theoretical work that takes a small step toward elucidation of such principles. A phenomenological model for the architecture of the epigenetic and genetic regulatory networks which describes diverse data obtained during reprogramming experiments will be presented. It is a Potts model (with short and long-ranged interactions) coupled to an Ising model (with short-range interactions). Importantly, our studies identify the rare temporal pathways that result in induced pluripotent cells. Further experimental tests of predictions emerging from our model should lead to fundamental advances, or negation of the model.

Over the last few years, nanoscopic systems, such as quantum corrals, Kondo droplets, or arrays of quantum dots, have provided a plethora of exciting novel phenomena arising from the interplay of quantum confinement, interactions and disorder. In this talk, I will present some recent theoretical results on non-equilibrium transport phenomena in arrays of quantum dots. In particular, I will show that the absence of self-averaging in nanoscopic systems yields scaling laws that are qualitatively different from those of mesoscopic or macroscopic systems. In addition, quantum confinement, giving rise to the presence of well-defined eigenmodes, can lead to interesting spatial current paths, including the possibility for current backflow. Finally, I will demonstrate how interactions can increase the current flow, suppress the effects of disorder, and neutralize the results of quantum confinement.

In the world of moderate Reynolds number, everyday turbulence of fluids flowing across planes and down pipes a velvet revolution is taking place.Experiments are almost as detailed as the numerical simulations, DNS is yielding exact numerical solutions that one dared not dream about a decade ago, and dynamical systems visualization of turbulent fluid's state space geometry is unexpectedly elegant. We shall take you on a tour of this newly breached, hitherto inaccessible territory. Mastery of fluid mechanics is no prerequisite, and perhaps a hindrance: the talk is aimed at anyone who had ever wondered why - if no cloud is ever seen twice - we know a cloud when we see one? And how do we turn that into mathematics?

Nonlinear wave patterns generated by an isolated steady pressure distribution moving across a water surface at speeds (Uc) below the minimum phase speed (Cmin) for linear gravity-capillary waves are explored experimentally. The pressure distribution is created by forcing air toward the water surface through a vertically oriented tube (internal diameter of 3 mm) that is mounted on a carriage that travels over the water surface. It is found that the wave patterns created are sensitive to both the air-flow rate and Uc. Several distinct wave patterns are found. At low values of Uc (< 0.83Cmin), the pattern is an isolated single depression that is centered on the pressure disturbance. The maximum depth of the depression increases slowly with carriage speed and the width of the depression is greater than its length in the flow direction. At a critical value of Uc , which depends on the air-flow rate, the pattern abruptly transitions to a second stable state in which the largest depression of the surface occurs behind the pressure disturbance. The maximum depth of the surface depression increases by a factor of about two over this transition and the following surface pattern looks very much like a freely propagating gravity-capillary lump. In the narrow transition zone between these states, the wave pattern is unsteady. As Uc is increased further, the depth of the depression decreases. The values of the maximum depth of the depression plotted versus Uc fall on a single curve in this region, independent of air flow rate. At still higher carriage speeds, Uc > 0.96Cmin, a third state is found with a V-shaped surface pattern that is similar to the pattern found for cases with Uc a little greater than Cmin. This state appears to be unsteady.

This work is being carried out in collaboration with T. Akylas and his research group at MIT who are performing numerical simulations of the flow.

In recent years we have become interested in the dynamics of magnetic particle suspensions subjected to biaxial and triaxial ac magnetic fields. For suspensions of spherical particles we have convinced ourselves (through theory, simulation and experiment) that we understand what is going on, including some pretty weird stuff. We have now started to study suspensions of magnetic platelets and have observed, under some very particular field conditions, the formation of extraordinary flow patterns and surface instabilities. We have no idea of what is going on, but we have made a lot of interesting videos that are fun to puzzle over.

Biaxial and triaxial ac magnetic fields are spatially uniform, time-dependent fields whose direction explores either two or three dimensions, with typical field component frequencies in the range of 100 - 1000 Hz and magnitudes from 0.005 - 0.05 T. In spherical particles suspensions a biaxial field creates negative dipolar interactions that lead to particle sheets, which are static structures of little interest. All of the really interesting phenomena -- fluid mixing [1], molecular-like particle clusterings [2], the formation of composites with exotic structures [3] -- occur in triaxial fields, which create complex many-body interactions.

We have discovered that magnetic platelets behave very differently, probably because of their tendency to rotate so as to confine the field vector to their plane. The resultant particle fluttering apparently creates complex flow because of hydrodynamic coupling. In the simplest case the flow can be described as a diagonal square lattice (relative to the directions of the field components) of "antiferromagnetic" flow cells, with the flow in each cell normal to the field plane. More complex flows can be stimulated, including helical flows, and these depend critically on both the frequency ratios of the field components and their phase relation. Understanding these flows is probably going to be a computational challenge of the first order, but their utility is clear: we can magnetically transport heat and mass at a terrific rate without a thermal gradient or gravity, and without pumps, hoses, connectors, seals or any moving parts. This has significant implications for cooling in space, or in any other circumstance where convection does not occur.

[1] J. E. Martin, Theory of strong intrinsic mixing of particle suspensions in vortex magnetic fields, Phys. Rev. E 79, 011503 (2009).

[2] J. E. Martin, E. Venturini, G. L. Gulley,* and J. Williamson, Using triaxial magnetic fields to create high susceptibility particle composites, Phys. Rev. E 69, 021508 (2004).

[3] J. E. Martin, R. A. Anderson, and R. L. Williamson, Generating strange magnetic and dielectric interactions: Classical molecules and particle foams, J. Chem. Phys. 118, (2003).

*Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed-Martin Company, for the UnitedStates Department of Energy under Contract No. DE-AC04-94AL85000. This work was supported by the Office of Basic Energy Research, DOE.

The phenomenon of drop impact displays a rich variety of behaviors throughout its large parameter space. Here, we focus on the specific regime of viscous liquid drops impacting on a smooth dry substrate. After impact, these drops form a thin pancake of uniform thickness. Using Volume-of-Fluid simulations, we find that this thickness is set by the growth of a viscous boundary layer, due to the no-slip conditions at the solid wall. The upper surface of the drop flattens down onto this interface, starting near the rim and moving inwards.

Remarkably, the evaporation of a droplet containing a nonvolatile solute creates a singular deposition profile: an arbitrarily large fraction of the solute becomes concentrated at the the perimeter. The density profile has a distinctive form, with a smooth fadeout at the trailing edge. We present a mechanism that predicts a power-law form for this profile. For the simplest and most common case, the predicted power is -7 as recently shown by Rui Zheng. This power can readily be varied. The power law is governed by the stagnation region of the lateral flow as the drop evaporates. It suffices to know two quantities: a) the evaporating flux J(0) at this stagnation point relative to its average over the drop and b) the height at the stagnation point relative to its average. We describe conditions for achieving a range of power laws. For a noncircular drop a single power law characterizes the deposition over the whole perimeter, despite the anisotropy of the stagnation flow. Another kind of novel controlled motion happens when an irregular object falls through a viscous liquid. These objects twist as they fall. Sufficiently extended objects twist in a way that depends on their shape but not their initial conditions, Nathan Krapf, Nathan Keim and I have shown.

Each new generation of supercomputer promises the ability to perform simulations on an unprecedented scale. As the size and complexity of supercomputers continues to increase, however, so too does the difficulty associated with effectively utilizing the new capability. I will discuss the results of three simulations that have made profitable use of the largest computers on earth: the solidification of a molten metal, the formation of a fluid instability and the dynamics of hot, dense plasma. In each case, a multidisciplinary team of physicists and computer scientists was able to overcome the substantial technical challenges involved and deliver simulations providing an unparalleled view into the physical behavior.

This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC5-07NA27344.

During the replication of many viruses, hundreds to thousands of protein subunits assemble around the viral nucleic acid to form a protein shell called a capsid. Most viruses must form a particular structure to be infectious and do so with astonishing fidelity. However, recent experiments demonstrate that capsids can assemble with different sizes and morphologies to accommodate nucleic acids or synthetic cargoes such as nanoparticles and inorganic polyelectrolytes. The assembly mechanisms that enable this combination of adaptability and precision are poorly understood.

The assembly of protein subunits into ordered capsid structures is a nonequilibrium process for which kinetics often trumps thermodynamic stability. In this talk, I will use Brownian dynamics simulations and dynamic Monte Carlo simulations with coarse-grained models for capsid proteins to explore the competition between kinetics and thermodynamics in two questions pertaining to capsid assembly and cargo encapsulation: (1) How do capsid proteins that faithfully form empty capsids (containing no cargo) with a single morphology assemble into different icosahedral morphologies around nanoparticles with different diameters? (2) How do capsid proteins assemble while simultaneously encapsulating a flexible polymer, and how much polymer can an assembling capsid package? In addition to suggesting answers to these questions, the simulations offer predictions that can be tested with both bulk and single molecule experiments. Time permitting, I will use a simple theory to investigate a third question: (3) How much can dynamic light scattering experiments reveal about the time scales of capsid assembly?

Cornstarch suspended in water has the remarkable mechanical property of shear thickening, in which the viscosity increases reversibly with shear rate. Using rheometry measurements we find shear thickening to be a generic property of suspensions of non-attractive particles. The severity of shear thickening, characterized by the slope of the viscosity curve, is found to diverge at a critical packing fraction corresponding to the jamming point. Videos of the shear profile show the shear thickening regime is a phase transition from a low stress phase where the particles remain unsheared to a high stress phase where all particles participate in shear flow. The videos also show dilation which suggests the dramatic increase in stress associated with shear thickening may be due to dilation against the confining pressure from surface tension. These connections between jamming, dilation, and shear thickening in suspensions may provide a way to connect behavior of many-particle systems from the colloid level to macroscopic dry grains.

Hydrodynamic instabilities at fluid interfaces are usually undesirable because of the detrimental effect they have on practical applications such as polymer processing and liquid-film coating. In this talk, two examples will be given in which such instabilities can actually be exploited for scientific and technological purposes. In the first example, we consider an instability that arises when a fluid flows past a soft elastic solid. Experiments and theory suggest that this instability may be responsible for certain rheological phenomena observed in surfactant solutions, and that it can also be useful for enhancing mixing in small-scale flows. In the second example, we gain insight into the surface-freezing phenomenon by considering an instability that occurs when the free surface of a liquid is oscillated vertically. Experiments show an abrupt change in instability characteristics at the onset of surface freezing, and theory indicates that this change corresponds to a transition from a free surface allowing slip to one where slip is absent. We also show that the instability can arise in viscoelastic liquids even in the absence of inertia, and derive a simple Mathieu equation which reveals that elasticity introduces an effective inertia.

Clustering of matter on the surface of lakes and pools and of oil slicks and seaweed on the sea surface is well-known empirically but there is no theory that describes it. Since surface flows are always compressible, such a theory should be based on the description of the development of density of inhomogeneities in a compressible flow. We studied the growth of small-scale inhomogeneities in the density of particles floating in weakly nonlinear small-amplitude surface waves. Despite the small amplitude, the accumulated effect of the long-time evolution may produce a strongly inhomogeneous distribution of the 'floaters': density fluctuations grow exponentially with a small but finite exponent. We have shown that the exponent is of sixth or higher order in wave amplitude. As a result, the inhomogeneities do not form within typical time scales of the natural environment. Thus the turbulence of surface waves is weakly compressible and alone it cannot be a realistic mechanism of the clustering of matter on liquid surfaces. However if besides waves there are also currents, the interplay of waves with currents, might be in some cases responsible for the patchiness of the floaters.

Swimming Escherichia coli responds to changes in temperature by modifying its motor behavior. Previous studies using populations of cells have shown that E.coli accumulate in spatial thermal gradients, but these experiments did not cleanly separate thermal responses from chemotactic responses. Here we have isolated the thermal behavior by studying the thermal impulse response of single, tethered cells. The motor output of cells was measured in response to small, impulsive increases in temperature, delivered by an infrared laser, over a range of ambient temperature (23 to 43 degrees C). The thermal impulse response at temperatures < 31 degrees C is similar to the chemotactic impulse response: both follow a similar time course, share the same directionality, and show biphasic characteristics. At temperatures > 31 degrees C, some cells show an inverted response, switching from warm- to cold-seeking behavior. The fraction of inverted responses increases nonlinearly with temperature, switching steeply at the preferred temperature of 37 degrees C.

Caenharbditis elegans also is thermotactic. We have developed a video-tracking microscope to follow movements of C. elegans as it freely crawls on the surface of an agar plate, and quantify this behavior using machine vision processing. A major challenge in analyzing animal behavior is to discover some underlying simplicity in complex motor actions. Here, we show that the space of shapes adopted by the nematode Caenorhabditis elegans is low dimensional, with just four dimensions accounting for 95% of the shape variance. These dimensions provide a quantitative description of worm behavior, and we partially reconstruct "equations of motion" for the dynamics in this space. These dynamics have multiple attractors, and we find that the worm visits these in a rapid and almost completely deterministic response to weak thermal stimuli. Stimulus-dependent correlations among the different modes suggest that one can generate more reliable behaviors by synchronizing stimuli to the state of the worm in shape space. We confirm this prediction, effectively "steering" the worm in real time.

This talk will describe three recent experiments on emergent patterns in three diverse physical systems. The overall shape and subsequent rippling instability of icicles is an interesting free-boundary growth problem. It has been linked theoretically to similar phenomena in stalactites. We attempted (with limited success) to grow ideal icicles and determine the motion of their ripples. Washboard road is the result of the instability of a flat granular surface under the action of rolling wheels. The rippling of the road, which is a major annoyance to drivers, sets in above a threshold speed and leads to waves which travel down the road. We studied these waves, which have their own interesting dynamics, both in the laboratory and using 2D molecular dynamics simulation. A viscous fluid, like syrup, falling onto a moving belt creates a novel device called a "fluid mechanical sewing machine." The belt breaks the rotational symmetry of the rope-coiling instability, leading to a rich zoo of states as a function of the belt speed and nozzle height.

here are some natural icicles 'http'://www.flickr.com/photos/nonlin/3566826271/ 'http'://www.flickr.com/photos/nonlin/3566826193/ 'http'://www.flickr.com/photos/nonlin/3587442026/

and lab icicles 'http'://www.flickr.com/photos/nonlin/3572193534/

washboard road in the lab 'http'://www.flickr.com/photos/nonlin/3697595615/ 'http'://www.flickr.com/photos/nonlin/3698410974/

in spacetime 'http'://www.flickr.com/photos/nonlin/3784441887/

Meandering syrup (movie) 'http'://www.flickr.com/photos/nonlin/3585645592/

Abstract: In this talk I will discuss the physical behavior of models on random graphs and its relation to real world systems. The most interesting feature, on which I shall focus, is a presence of an ideal glass phase amenable to analytic description. After describing the computational method, I will present two applications:

(1) Random optimization problems where the presence and properties of the glassy phase are related to the average algorithmical hardness.

(2) A particle model motivated by the patchy colloidal particles, that reproduces some interesting features of the observed phase diagrams of colloidal systems.

In building models of complex systems and networks, one has sparse measurements from which one must infer unknown parameters at the nodes and links as well as the unobserved state of the system if predictions are to be made. When these systems are nonlinear chaotic oscillations of the networks impede the ability to achieve these goals, and one must regularize the procedure to stabilize the transmission of information from the observations to the model. We will discuss this in a general context and demonstrate how the solution works in practice in the context of electronic circuits, and for a small geophysical model.

We also consider the formulation of this problem for when there is noisy data, errors in the model, and uncertain initial conditions. This formualtion is a statistical physics problem, and we demonstrate that the effective action for this problem is a systematic wasy to evaluate all the conditional means and covariances required for the estimations.

Many potential applications of nanomaterials involve conductivity and possibly coherent wavefunctions across nanometer building blocks. At present, the conductance of solids of quantum dot nanocrystals exhibits hopping with strong effects of temperature, bias and electronic occupation. The Variable Range Hopping model successfully accounts for the data, but a consensus is still lacking. A magnetic field also affects the conductivity by squeezing the wavefunction and blocking spin relaxation.

Evolution works through natural selection of the fittest versions of genes (a.k.a. alleles) in populations. Yet, the fitness of an individual is determined by its genotype which includes all of its genes so that ``bad" alleles can hide behind the ``good" ones. Sex and recombination can eliminate this hitch-hiking effect, but in its turn has an adverse effect of breaking up beneficial interactions between alleles often resulting in low fitness progeny. This talk will focus on the rather non-trivial dynamics of selection in the presence of gene interactions and recombination and expose connections with the familiar problems of statistical physics. We will see that selection dynamics has two distinct phases and will calculate how recombination accelerates the rate of evolution.

Since radiocarbon dating was first demonstrated in 1949, the field of trace analyses of long-lived cosmogenic isotopes has seen steady growth in both analytical methods and applicable isotopes. The impact of such analyses has reached a wide range of scientific and technological areas. A new method, named Atom Trap Trace Analysis (ATTA), was developed by our group and used to analyze Kr-81 (t_1/2 = 2.3x10^5 years, isotopic abundance ~ 1x10^-12) in environmental samples. In this method, individual Kr-81 atoms are selectively captured and detected with a laser-based atom trap. Kr-81 is produced by cosmic rays in the upper atmosphere. It is the ideal tracer for dating ice and groundwater in the age range of 10^4-10^6 years. As the first real-world application of ATTA, we have determined the mean residence time of the old groundwater in the Nubian Aquifer located underneath the Sahara Desert. Moreover, this method of capturing and probing atoms of rare isotopes is also applied to experiments that study exotic nuclear structure and test fundamental symmetries.

I will argue that experimental studies of quantum phase transitions have highlighted a number of theoretical problems which cannot be addressed by the traditional methods of many body theory. Near the superfluid-insulator transition, studied in ultracold atom systems, we have a regime where transport coefficients are determined completely by fundamental constants of nature; however, we have been unable to make this connection numerically precise. In the high temperature superconductors, and a number of other compounds, we are faced with quantum phase transitions involving the breakup of the Fermi surface: traditional methods fail because of the singular effects of the many low energy excitations near the Fermi surface. I will then present an elementary introduction to the AdS/CFT correspondence, which was discovered by string theorists. I will show how it has already made remarkable progress in describing transport near quantum critical points. Recent progress suggests that it may also shed light on quantum phase transitions of systems with Fermi surfaces.

Thermal convection has come to be regarded as one of the most important archetype systems of dynamical systems. It has been extensively studied over the past 3 decades or so. An experimental system often consists of a fluid confined within a rigid box that is heated at the bottom and cooled at the top. Our experimental studies explore the intriguing phenomena when its rigid boundary is partly replaced either by a freely moving, thermally opaque (which reduces local heat loss) "floater" or by a collection of free-rolling spheres. We identify from our table-top experiments several dynamical states, ranging from oscillation to localization and to intermittency. A phenomenological, low-dimensional model seems to reproduce most of the experimental results. Our on-going experiments are inspired by the geophysical process of continental drift, where the mantle is regarded as the convective fluid and the continents as mobile "thermal-blankets.

The discovery of scaling laws for the global heat transport, large-scale velocity and local temperature statistics in turbulent Rayleigh-Benard convection has stimulated considerable experimental and theoretical efforts, aimed at understanding the universal nature of the observed scaling laws. Because of historical reasons, most of the convection experiments were conducted in upright cylindrical cells with small aspect ratios. An important question one might ask is: To what extend are these scaling laws universal and independent of the cell geometry? Understanding of this question has important implications to large-scale astro/geophysical convection, such as that in the atmosphere and oceans, in which boundary effects are usually less important. In this talk, I will report a systematic experimental study of turbulent convection in a horizontal cylinder with the bottom 1/3 (curved) surface heated and the top 1/3 (curved) surface cooled. The measurements are conducted with varying aspect ratios and Rayleigh numbers. The experiment reveals important geometric effects on the scaling laws and coherent oscillations in turbulent thermal convection.

This work is done in collaboration with Hao Song and is supported by the Research Grants Council of Hong Kong SAR.

Soft solids placed under compressive stress can undergo a surface buckling instability leading to formation of sharply-folded creases on their free surfaces. We study a particular example of this instability that occurs upon swelling of crosslinked polymer networks on rigid substrates; when placed in contact with solvent, they are subjected to compressive swelling stresses due to the constraint against lateral expansion imposed by the substrate. We have studied a series of surface-attached hydrogels and found the conditions for instability to be rather insensitive to material properties or layer thickness, in accord with simple predictions. Using temperature-responsive gels, we seek to elucidate the mechanism of crease formation and growth, as well as the evolution of crease structures. Finally, we take advantage of this instability as a way to create dynamic polymer surfaces with reconfigurable chemical patterns.

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William Irvine (12:30pm, KPTC 206)

New York University

william.irvine at gmail.com

'Title': Light geometry and soft condensed matter assembly

Charged PMMA colloids on an oil (Cyclohexyl bromide) water interface interact via a screened coulomb interaction and arrange into a crystalline lattice. The interface can be subject to designer optical fields to study the behavior of a lattice in ordered and disordered potentials. Furthermore I will show how light fields can be designed to `tweeze' individual topological defects and study the dance of dislocations involved in the birth and reversal of a grain. By creating curved oil-water interfaces having positive, negative and varying Gaussian curvature as well as different Euler numbers, we study the influence of curvature on the distribution and dynamics of topological defects. The crystals on curved surfaces are imaged and manipulated using a setup capable of simultaneous holographic optical tweezing and confocal imaging. I will also briefly discuss a system of lock and key colloids in which the geometry oft surfaces of colloidal particles can be used to direct their self assembly into a variety of structures.

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Silke Henkes (2:00pm, GCIS E223)

University of Leiden

henkes at lorentz.leidenuniv.nl

'Title': Friction and Failure: the role of critical contacts in the frictional jamming transistion

How can we relate microscopic failure at the contact level when the frictional force reaches the Coulomb threshold to the global stability properties of frictional packings? We show that these critical contacts modify the constraint counting and lead to an generalized isostatic line, instead of the isostatic point familiar from frictionless jamming. This can explain the range of contact numbers observed at frictional jamming. We probe the dynamics of failure near this transition for two 'situations': isotropic packings and a tilted bed undergoing an avalanche. In the isotropic case, we find that letting critical contacts slip crucially affects linear response. We recover soft modes, and the plateau of the density of states scales with the distance to generalized isostaticity, closely mirroring the frictionless case. For the avalanching bed, we find that correlated clusters of particles with critical contacts are responsible for most of the failure events in the creeping phase before the onset of the avalanche. These clusters are always generalized isostatic, and both their number and typical size show a sharp upturn just before the system avalanches. We conclude that through the generalized isostaticity concept, critical contacts are crucial to understanding the jamming transition in frictional packings.

Maxwell's equations allow for remarkable solutions having linked and knotted field lines. A particularly striking solution is one characterized by the property that all electric and magnetic field lines are closed loops with any two electric(magnetic) field lines linked. These little known solutions, are based on the Hopf fibration and have a remarkably simple representation in terms of self-dual Chandrasekhar-Kendall curl eigenstates. I will discuss their structure, time evolution, physical properties, generalization and how they may be physically realizable.

Crumpled papers, wrinkled skins, and buckled plant leaves are few familiar examples of the rich variety of patterns that elastic membranes may exhibit under quite featureless constraints. One may ask: Does a morphological "phase space" exist, according to which the many possible membrane patterns are classified? What are the relevant parameters that determine whether a distribution of forces and constraints gives rise to a smooth shape (e.g. periodic wrinkles) or to an irregular one, characterized by localized ridges and vertices (e.g. crumpled sheets)? In this talk I will address these questions, by focusing on an elementary case: highly-symmetric membrane (homogenous, isotropic, of rectangular shape) that is buckled under uniaxial compression and is subjected to a uniform tension in the orthogonal direction. I will show that a surprisingly rich "phase diagram" of distinct morphologies is spanned by a pair of dimensionless parameters that encapsulate the relevant mechanical conditions and geometric constraints. In particular, a novel series of "period fissioning" instabilities gives rise to a new type of wrinkling cascade when the tension is sufficiently large. This instability mechanism is shown to underlie a recently-discovered phenomenon: A smooth cascade of wrinkles, in uniaxialy-compressed ultrathin membranes, floating on liquid and subject to tension and geometric frustration due to strong capillary forces.

We demonstrate that the dynamical jamming transition that occurs for finite-ranged repulsive particles as a function of temperature, packing fraction, and applied stress can be collapsed onto a universal form near the zero-temperature jamming transition. We show that the rheology and the relaxation time for a class of models at arbitrary temperature and shear stress approach hard sphere scaling functions at low pressure. We find the shape of the universal jamming surface as a function of two ratios, the ratio of temperature to the product of pressure and the particle volume, and the ratio of shear stress to pressure.

In the large cells of many eukaryotic organisms, especially those of aquatic and terrestrial plants, the fluid contents are observed to be in constant motion. This "cytoplasmic streaming" was described first in 1774 by Bonaventura Corti, and while the molecular mechanism that drive it are now rather clear, its role in cellular physiology is still rather mysterious. In this talk I will describe a combination of experimental and theoretical work aimed at solving this mystery. A fundamental feature of such flows is that they can be sufficiently fast that the Peclet number can greatly exceed unity, a very different regime than that usually considered in cellular biophysics. This suggests the possibility that streaming promotes mixing within cell. Indeed, we find that one of archetypal geometries of fluid circulation in plants, rotational streaming driven by helical arrangements of molecular motors at the cell periphery, can enhance mixing in much the same way as certain geometries that have been explored in the field of microfluidics. Cytoplasmic streaming also interacts very strongly with the tonoplast, the lipid membrane that encloses the vacuole, raising a whole host of fascinating issues in the hydrodynamics of membranes that will be outlined.

We present experimental and numerical studies of the behavior of the Belousov-Zhabotinsky (BZ) chemical reaction in flows with chaotic mixing. Experiments with the excitable BZ reaction are used to determine the effects of fluid mixing on the motion of reaction fronts. Moving vortices in the flow tend to pin and drag the reaction front, a result that leads to mode-locking of fronts in a flow with periodically-oscillating vortices. An extension to theoretical treatment of chaotic mixing involving .burning lobes. is used to explain the measured front propagation behavior. Manifolds characterizing chaotic mixing also help explain the patterns that form for oscillatory reactions in both two- and three-dimensional flows with chaotic mixing. We also discuss pinning (freezing) of reaction fronts by vortices (both regular and random patterns) when propagating against an imposed"wind," similar in some respects to pinning of charge-density waves in the presence of an imposed electric field. Time permitting, we will also discuss experiments conducted on synchronization of extended advection-reaction-diffusion systems via superdiffusive transport and Levy flights.

In the bicentennial year of the birth of Charles Darwin, we are reminded that he invoked the incompleteness of the geological record to reconcile paleontological observations with his expectations. As early as 1860, however, Darwin's pessimistic view of the quality of the geological record had already been questioned. Rather than trying to resolve the issue based on the data available 150 years ago, let us jump forward to the 21st century and consider some of the major advances that allow us to cope with paleontological incompleteness. First, geologists simply know more of the fossil record than they did then. Whole new regions have been explored, for example, and the record of pre-Cambrian and Cambrian strata has been documented in great detail. Second, geological and paleontological data have been archived in ways that enable systematic retrieval and analysis. Finally, paleontologists and stratigraphers have developed tools for quantifying the degree of completeness of the record and for circumventing many of the biasing effects of incompleteness. I will focus on this last development, using models of incomplete sampling and computational approaches to show how paleontologists have turned the raw data from the imperfect record into estimates of parameters of evolutionary interest, such as rates of taxonomic origination and extinction.

A variety of natural growth processes, including viscous fingering, electrodeposition, and solidification can be modeled in terms of Laplacian growth. Laplacian growth patterns are formed when the boundary of a domain moves with a velocity proportional to the gradient of a harmonic field, which satisfies the Laplace equation outside of the domain. A simple model of Laplacian growth is considered, in which the growth takes place only at the tips of long, thin fingers. Following Carleson and Makarov (J. Anal. Math. 87, 103, 2002), the evolution of the fingers is studied with use of the deterministic Loewner equation. The method is then extended to study the growth in a linear channel with reflecting sidewalls. One- and two-finger solutions are found and analyzed. It turns out that the presence of the walls has a significant influence on the shapes of the fingers and the dynamics of the screening process, in which longer fingers suppress the growth of the shorter ones. Possible experimental realizations of the model are discussed, including combustion in Hele-Shaw cell and channel formation in dissolving rock fractures.

I will present a theoretical and numerical investigation of the role of air cushioning droplet impacts on dry rigid surfaces. This study is motivated by the observations that reducing the ambient air pressure can suppress splashing (Xu, Zhang and Nagel, Phys. Rev. Lett., v94(18), 184505, 2005). This cushioning occurs during a microsecond, when the droplet is within 1 micron distance from the surface. We hypothesize that contact with the surface determines whether the droplet splashes or not. The dominant forces acting during the impact are the inertia of the drop, and the viscous and compressible resistance to draining the air cushion. Due to the air cushion, the droplet deforms during impact and attempts contact on a rim trapping a bubble. However, the dominance of the aforementioned forces is not asymptotically consistent; initially negligible forces like surface tension, etc. become important and change the dynamics. As a result, before contacting the surface, the droplet interface overturn on itself indicating the ejection of a liquid lamella. We predict that for an ethanol droplet of radius 1.7 mm moving at 3.7 m/s in 1 atm ambient pressure, the lamella is ejected on a rim at a radial distance of about 100 microns, when the center of the drop is 0.5 micron from the surface. We believe that this lamella subsequently forms the crown of the splash.

When an unstable iceberg tips over, it makes waves in the surrounding water that can (a) stimulate other icebergs to capsize and (b) cause calving of new unstable icebergs from surrounding glacier termini. This fact causes Wendy Zhang and I to wonder if the dynamics of ice-shelf disintegration in Antarctica can be understood as a .mass capsize catastrophe. applicable to arrays of orientation-changeable objects that interact via waves in an intervening medium. My presentation will outline the computational approaches to one of the most reduced sub-questions of the ice-shelf disintegration problem: What is the amplitude and frequency distribution of waves created by capsize of a single iceberg in otherwise quiet, undisturbed water? I discuss the strengths and weaknesses of three numerical approaches: "meshed" finite-element and finite-difference methods, "meshless",

smooth particle hydrodynamics (SPH) methods, and a "contour integral",

method based on Green's second identity.

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We can treat the behavior of many-atom systems in terms of how they move on an effective potential surface of 3N-6 independent variables and one dependent variable, the internal energy, for a system of N atoms. This is adequate for most dielectric systems; collections of metal atoms are more complex and sometimes require considering multiple potential surfaces. However, restricting ourselves to dielectrics, at least to get into the subject, we recognize that we face a problem of trying to understand what goes on in a space of very many dimensions, if we want to treat anything beyond the very simplest systems. We find ourselves confronting such questions as, "Why can some systems, cooled from their liquid state, invariably find their way to special, often well-ordered structures, while others 'get lost' in any of a large number of amorphous structures?" This is obviously related to the issue of protein folding, among others. Can we characterize such surfaces in terms of their stationary points? Can we use master equations to describe what happens on these surfaces, in terms of their well-to-well kinetics? How is the topography of a multidimensional potential related to the interparticle forces? These are some of the issues we face in trying to address a challenge of true complexity.

State estimation techniques are used in weather and climate prediction, hydrogeology, seismology, as a way to blend model output and real data in order to improve on predictions from the exclusive use of the model or the data alone. Techniques that are based upon least-squares ideas, such as the family of Kalman Filter/Smoothers, or Variational Data Assimilation, are optimal in linear/Gaussian problems. However, they often fail in problems in which nonlinearities are important and/or when Gaussianity in the statistics cannot be assumed. Even linearization may fail, and so do ensemble techniques that make nonlinear predictions but rely on linear analyses. These comprise the practical state of the art, at least in weather forecasting and in hydrogeology. I will describe these as well as how failures arise in these methods. We have created a number of nonlinear/non-Gaussian data assimilation techniques. Our present efforts are to make them computationally practical as well as to use of these to do problems that are otherwise intractable using conventional means. One such application is in Lagrangian data assimilation: here we tackle the problem of blending data that has been sampled along paths, which when blended in traditional ways on Eulerian grids will lead to loss of critical features even though the estimates may be variance-minimizing.

The Swift parallel scripting language lets users apply parallel composition constructs to existing sequential or parallel programs to express highly parallel scripts. Swift scripts are flexible and portable, and can run efficiently on platforms ranging from multicore workstations to petascale supercomputers. For performing parameter sweeps and data analysis with exiting application programs, parallel scripting is typically easier and more productive than tightly-coupled parallel programming. This talk will give an overview of Swift and how its used to run scientific applications in parallel on clusters, grids, clouds, and petascale systems. The architectural challenges of scripting on large-scale systems will be covered, and case studies will be presented.

The carbon cycle describes the transformations of carbon as it cycles through living organisms and the physical environment. Understanding its rates of change is fundamental to problems ranging from the evolution of life to modern climate change. A key aspect of these problems concerns the rates at which organic detritus is converted to carbon dioxide. Observations---in forests, in the oceans, and in sediments at time scales ranging from days to millions of years---show that apparent rates systematically slow down with increasing detrital age. We show how these observations can be quantitatively related to biological and environmental heterogeneity, and suggest ways in which our results may prove useful for understanding past and present changes in carbon dioxide levels.

About 252 million years ago, as the Permian period gave way to the Triassic, roughly 90% of all living species disappeared from the fossil record. This event, the most severe extinction in Earth history, was accompanied by a rapid (~10,000 year) change in the carbon isotopic composition of seawater. By transforming these chemical changes to physical fluxes, we show that the isotopic event is consistent with an incipient singularity in the growth of the oceans' reservoir of dissolved inorganic carbon. The singular influx of carbon dioxide into the oceans indicates a fundamental nonlinearity in Earth's carbon cycle. Its identification suggests that any hypothesis for the extinction's cause should predict such a blow-up. We identify a biological mechanism with this property and discuss its relevance to observations.

While information processing takes place across many levels of biological organization, the coordination of interaction specificities within cellular networks plays a central role. The problem of molecular discrimination is a key element in many regulatory and signaling pathways, but is compounded by the coexistence of many homologous molecules that interact with similar sets of substrates, leaving systems vulnerable to potential crosstalk between pathways. Interpreting such phenomena in the context of constraint satisfaction problems that arise at the interface of computer science and statistical physics reveals unusual geometric structures in high-dimensional genotype spaces that might be used to negotiate tradeoffs between system robustness and fragility.

Biological membranes define the outer boundary of living systems and mediate transport and communication between the cell and its surroundings. They defend the cell against invasive agents, and most present day drugs interact with membrane components. While biological membranes are critical features of functioning cells, their complexity renders many of their characteristics impenetrable to fundamental physical studies. In my presentation I will demonstrate how the neutron reflectometry can be applied to study model lipid membranes in bulk water. In particular I will discuss how neutron reflectometry can be used to probe the stability of mixed sphingomyelin/cholesterol (SM/Chol) bilayers during their interactions with b-cyclodextrin. The SM/Chol complexes are thought to be major constituents of so called .lipid rafts. which have been implicated in many cell functions such as endocytosis, signaling, and lipid regulation.

Super-cooling a liquid often produces glass -- a solid with no apparent structural order. Unlike crystallization, a glass transition is not accompanied by a thermodynamic singularity. Nevertheless, a phase transition can underlie the formation of glass. Unlike equilibrium order-disorder phenomena, this transition appears as a singularity in a partition function of dynamical histories. I describe this transition -- its order parameters and phase diagrams.

The statistical physics of trajectory space has a distinguished history -- from Onsager's formulation of non-equilibrium thermodynamics, to Martin-Siggia-Rose theory, and so on. In recent years, it has provided principles that, among other things, facilitate computer simulations of rare events, and numerical studies of non-equilibrium phase transitions. I describe this development and its applications in a few illustrative cases.

A function traditionally attributed to articular cartilage, the soft connective tissue covering bones in joints, is to dissipate energy from impact loading. This idea, however, came into question in the 1970's with the recognition that articular cartilage is no more effective than trabecular bone at reducing the peak impact force of a sudden compressive load. On the other hand, articular cartilage is exposed to shear loading as well as compressive loading during joint articulation. In fact, shear stresses in articular cartilage are known to be a major cause of joint damage and disease. The energy absorbing capacity of this tissue under shear has received little attention. Furthermore, the inhomogeneous structure and composition of this tissue suggest a heterogeneous capacity to dissipate energy that remains largely unstudied. In this talk I will show that using a Tissue Deformation Imaging Stage in conjunction with fast confocal microscopy allows for determining the depth dependence of the shear mechanical properties of articular cartilage. Using these novel techniques we have been able to determine that nearly all of the shear energy is dissipated in a 300 micron thick region located 100 microns below the articular surface. Finally, I will comment on the relevance of this finding to diseases such as Osteoarthritis as well as some of the medical procedures that are currently being practiced.

Ideas about evolution were first formulated before biology and genetics developed into the sophisticated sciences they are today. Molecular biology has had a profound impact on our understanding of how organisms are related to each other and how they change over time. Genome sequencing reveals the evolutionary record as it remains in the DNA of living organisms and constitutes a test of theories about how evolution has occurred. Discoveries about the molecular and cellular nature of evolutionary changes show that this remains a vital and exciting area of science with many new theoretical and experimental possibilities. In particular, genome sequences teach us that many key events in evolution have been accompanied by major and rapid changes in the content and organization of cell DNA that affected numerous characters at the same time. These kinds of changes were unknowable to the pioneers of evolutionary thinking and have not yet been included in conventional statements about how the evolutionary process operates. Incorporating lessons from the DNA record, recent observations of evolution in action, and experiments about the biological processes of genome change make it possible to formulate a 21st Century view that is consistent with other developments in the molecular life sciences.

The crucial feature of neuronal ensembles is their high complexity and variability. This makes modelling and computation very difficult, in particular for detailed models based on first principles. The problem starts with modelling geometry, which has to extract the essential features from those highly complex and variable phenotypes and at the same time has to take in to account the stochastic variability. Moreover, models of the highly complex processes which are living on these geometries are far from being well established, since those are highly complex too and couple on a hierarchy of scales in space and time. Simulating such systems always puts the whole approach to test, including modeling, numerical methods and software implementations. In combination with validation based on experimental data, all components have to be enhanced to reach a reliable solving strategy. To handle problems of this complexity, new mathematical methods and software tools are required. In recent years, new approaches such as parallel adaptive multigrid methods and corresponding software tools have been developed allowing to treat problems of huge complexity. In the lecture we present a three dimensional model of signaling in neurons. First we show a method for the reconstruction of the geomety of cells and subcellular structures as three dimensional objects. With this tool, NeuRA, complex geometries of neuron nuclei were reconstructed. We present the results and discuss reasons for the complicated shapes. We further present a tool for the automatic generation of realistic networks of neurons (NeuGen). We then present a model of calcium signaling to the nucleus and show simulation results on reconstructed nuclear geometries. We discuss the implications of these simulations. We further show reconstructed cell geometries and simulations with a three dimensional active model of signal transduction in the cell which is derived from the Maxwell equations and uses generalized Hodgkin-Huxley fluxes for the description of the ion channels.

The phase behavior of hard, spherical particles is, by now, well understood. However, the dense phases of soft particles can be surprisingly different from the simple crystal structures that are formed by atoms or colloids. In my talk I will discuss two unusual phases that can be formed by soft particles: one such phase is observed in the case of very "soft" nano-colloids. Such particles may form a completely novel class of crystals: so-called "cluster solids". The second system that I will discuss consists of colloids coated with a "corona" of long DNA strands. These systems can undergo a curious condensation transition that has no counterpart in systems of simple atoms or molecules. In my talk I will discuss how computer simulations can be used to gain insight in the unusual physical properties of these materials.

In this talk I will describe two innovative programs in postgraduate education. The first is the African Institute for Mathematical Sciences (AIMS), in Cape Town, South Africa. AIMS has developed a unique teaching model whose goal is toenable outstanding graduates, recruited from across Africa, to become independent thinkers and problem-solvers across the full spectrum of science and engineering, feeding into research, academia, industry and government. Since 2003 over 300 students, from 30 African countries and including 75 women, have passed through AIMS doors. The vast majority have continued to successful scientific and technical careers, most in Africa. It is now proposed to scale AIMS up to a network of 15 centres continent-wide, over the next decade. This proposal, dubbed the AIMS Next Einstein Initiative, is winning widespread interest andsupport. The second is the Perimeter Scholars International (PSI) program, recently initiated at the Perimeter Institute for Theoretical Physics. Learning from many successful elements of the AIMS program, PSI is an attempt to renew and refresh the teaching of advanced theoretical physics, making this fundamental field more attractive, interesting, exciting and useful for students recruited from around the world. The experience of developing new approaches to the teaching of mathematical science holds many lessons: of the power of mathematical ideas to bridge cultures, and of the need to do more to attract and enable bright students to pursue advanced scientific learning.

Bacteria sense and respond to environmental stimuli, or signals, through a simple class of regulatory circuits consisting of an upstream sensory protein and a down stream response regulator. These .two-component systems. play a central role in regulating adaptive responses to diverse environmental signals and are found in remarkable numbers within individual organisms and across different bacterial species. Two-component systems show considerable variability in their degree of complexity, but even the simplest examples have interesting and subtle design features. After a general introduction to bacterial signal transduction, I will describe modeling and experimental work on E. coli in which we have explored implications of the phosphorylation cycle that is found in many of these circuits. I will primarily focus on mechanisms that maintain signal strength and provide insulation against cross-talk.

Really random solids -- such as those commonly formed via the vulcanization of polymers or the random chemical bonding of small molecules -- are materials that have architectures that are as unsymmetrical as can be. Nevertheless, they exhibit certain surprisingly universal characteristics -- structural and elastic -- that are not exhibited by their apparently simpler cousins, the crystalline solids. In this talk, I shall discuss the main ideas that go into constructing a simple, Landau-style approach to the structure and elasticity of really random solids. I shall focus on how these universal characteristics, and especially their probabilistic nature, can be readily encoded -- and hence computed -- within a framework that involves not one but many copies (or replicas) of the space in which the constituent particles move. By drawing on examples from polymer and liquid-crystal science, I hope to show that this Landau-style approach enables the development of a unified view of the percolative, structural, and elastic characteristics of many types of really random solid.

Animal groups, such as bird flocks, fish schools, or insect swarms, often exhibit complex, coordinated collective dynamics resulting from individual interactions. While there has been a growing interest in this emergent behavior, there are only a handful of experiments that study swarms in a controlled environment. In this talk, I will present theoretical advances stemming from new interactive fish schooling experiments recently set up in collaboration with Prof. I. Couzin and his group at Princeton University. Using results from these experiments and previously gathered data on the collective motion of locusts, I will characterize different swarming states from a non-equilibrium statistical physics perspective, highlighting specific and universal properties that stem from dynamical and evolutionary constraints

Lynn Margulis has studied the role of symbiosis in evolution for the last five decades. Her defense of the symbiogenetic hypothesis was vindicated in the 1980s when organelle DNA sequencing demonstrated that mitochondria and chloroplasts are descendants of endosymbiotic bacteria. She has continued to challenge conventional wisdom and argue for symbiotic events in the evolution of organelles that no longer contain their own DNA. One of the leading non-Darwinian evolutionists, Lynn Margulis always introduces new information and new ways of thinking scientifically about less widely known biological processes in evolutionary change.

Piezo-acoustic inkjet printing has become a mature technique for high performance printing. Nevertheless, there are still various scientific challenges. In this talk I will cover some of them: (i) Coupling between the fluid dynamics and the acoustics, in particular when a disturbing bubble has been entrained in the ink channel. (ii) Optical and acoustical monitoring of the bubble. (iii) Mechanisms of the bubble entrainment. (iv) Droplet formation and pinch-off of droplets. (v) Droplet impact on substrates. The work has been done in close collaboration with Oce.

I present a fundamental theory for the kinetics of systems of classical particles. The theory represents a unification of kinetic theory, Brownian motion, and field theory. It is self-consistent and is the dynamic generalization of the functional theory of fluids in equilibrium. This gives one a powerful tool for investigating the existence of ergodic-nonergodic transitions near the liquid-glass transition. I will discuss recent progress in understanding the nature of the liquid-glass transition.

Understanding how the brain works has remained a formidable challenge that holds the promise for fundamental change in the human condition. Neuroscience has become a truly interdisciplinary field of research where some of the most substantial progress has resulted from the combined application of computational and experimental approaches. In this talk, I am going to show how computational neuroscience embedded in an experimental context has revealed novel mechanisms of how structured brain activity emerges. The overall goals of the talk are to (1) provide an introduction to the brain and in particular to cortex as a fascinating dynamics system, (2) demonstrate the role and benefits of computational neuroscience, and (3) motivate further interdisciplinary work between simulations/theory and experiments.

In contrast to water-in-air break-up, which approaches universal dynamics regardless of initial or boundary conditions, the pinch-off of air-in-water maintains a memory of azimuthal asymmetries until the final moment. For such a memory to persist, the vertical flow in the pinch-off neck region must become negligible as break-up approaches; a significant vertical flow would sweep azimuthal asymmetries out of the minimum and erase memory. Previous studies focused on situations where this requirement can be satisfied easily: As the bubble begins to break apart, its neck profile near the minimum evolves towards two slender cones smoothly joined at the apex. This dynamics, characterized by a logarithmically slow decrease in the cone angle, is vulnerable to azimuthal asymmetries. This leaves open the question of whether a memory-erasing vertical flow can be created by causing the neck profile to evolve towards a shape with large and/or asymmetric cone angles. Using a boundary-integral simulation, we show that this does not in fact happen. When the two initial cone angles are equal, the vertical flow acts to reduce the angles. When the two cone angles are different, the vertical flow is comprised of a translation and a rolling motion. The neck minimum quickly shifts towards the smaller-angle cone, causing a new, symmetric neck to form with cone angle close in value to the smaller initial angle. In all cases, the adjustment towards a slender neck is rapid, occurring as the minimum reduces by only a factor of 10. As a result, all initial states evolve toward a regime where the vertical flow is much weaker than the radial flow. Therefore, all bubble shapes support memory-encoding vibrations.

Suppose that the variability in our movements is caused not by noise in muscle contraction, nor by fluctuations in our intentions or plans, but rather by errors in our sensory estimates of the external parameters that define the appropriate action. For tasks where precision is at a premium, performance would be optimal if no noise were added in movement planning and execution: motor output would be as accurate as possible given the quality of sensory inputs. We have used visually-guided smooth pursuit eye movements in primates as a testing ground for this notion of optimality. In response to repeated presentations of identical target motions, nearly 92% of the variance in eye trajectory can be accounted for as a consequence of errors in sensory estimates of the speed, direction and timing of target motion, plus a small background noise that is observed both during eye movements and during fixations. The magnitudes of the inferred sensory errors agree with the observed thresholds for sensory discrimination by perceptual systems, suggesting that these very different neural processes are limited by the same noise sources. Computing the signal to noise ratio of pursuit movements allows us to estimate a .behavioral threshold. akin to a threshold for reliable perceptual discrimination of a change in target motion. We find that pursuit thresholds agree quite well with perceptual thresholds throughout the sensory-driven period of movement initiation. These results suggest that pursuit can be a reliable read-out of the evolving sensory estimate of target motion.

A gel is a meshwork of cross-linked polymers, permeated by solvent. We model the gel as a stretched elastic network of Lennard-Jones (ELJ) particles in two dimensions and study it by molecular dynamics simulations. When temperature is reduced below a threshold value, the gel undergoes large-scale reorganization and percolating strings (high density clusters) appear in the system and form a super-network. The discontinuous transition exhibits hysteresis and is accompanied by a jump in the elastic modulus. We explore the phase diagram, identify the range of parameters in which micro-phase separation is observed and propose some tentative ideas concerning the physical mechanisms leading to the formation of string-like clusters. Finally, we examine the effects of network heterogeneity and present preliminary results on three dimensional ELJ networks.

This seminar will present a number of the theoretical techniques we have developed to solve the Schroedinger equation for ground and excited states, including collisions and multiparticle continua. Some of the methods that we have combined in unusual ways include correlated Gaussian basis sets, diffusion quantum Monte Carlo, hyperspherical coordinate formulations, and multichannel quantum defect ideas. These tools, when used appropriately, substantially extend the range of problems amenable to theoretical description. In addition to discussing how these various methods permit the calculation of quantitative observables, I will stress the qualitative and semi-quantitative insights they provide into underlying dynamical mechanisms.

Traumatic Brain Injury (TBI) describes injury to the brain that is not necessarily accompanied by skull fracture and includes the full range of severities from mild concussions to permanent cognitive impairment. Head impacts from motor vehicle and sports injuries are the leading causes of civilian TBI, but TBI is also common among military personnel exposed to blast waves, with estimates placing upwards of 20% of returning US soldiers from recent combat missions affected. Current helmets do not adequately protect against TBI for either impacts or blasts. There are conceptual shortcomings in the measures of protection and inadequate standards even for aspects of impact protection that are understood. For blasts, the problem is even more fundamental as there has been a lack of understanding of the actual injury mechanism. I will discuss results of computations and numerical simulations that study the interaction of blast waves with toy models of the skull and reveal a skull flexure induced injury mechanism distinct from that of the bulk acceleration injury associated with head impacts. I will discuss the long term implications of these distinct mechanisms for helmet design and clinical diagnosis. An underlying theme is to highlight the opportunity for a physics perspective in this subject.

We are interested in developing and using microfluidics for high-throughput studies in development, cancer and immunology. In this talk, I will show a microfluidic system for arraying, aligning/orienting, and imaging embryos to study the signaling in embryonic development. We use a similar principle to manipulate cells and perform long-term imaging of cells under a variety of conditions to study, for example, calcium dynamics in cellular response to oxidative stress. The advantage of this approach is that we have robust particle loading (very high loading occupancy and high single cell/particle/embryo loading efficiency) in a short amount of time just using flow passively. In a parallel example, we use microfluidics to study early signaling event in T cell activation. Cells/particles interact with fluids especially in complex flow (e.g. chaotic flow) and it makes mixing difficult in some instances. On the other hand, these interactions can be exploited to perform separation. I will present a fast and inexpensive method to image fast flowing particles in flow as well as results of some studies of T cell replicative senescence using this system.

Sterols are essential membrane bilayer components in all eukaryotic cells, and their abundance is tightly regulated by manifold feedback pathways. I will present evidence that these homeostatic mechanisms respond to a common signal: active membrane cholesterol. Active cholesterol is that fraction which exceeds the complexing capacity of the polar bilayer lipids. Increments in plasma membrane cholesterol exceeding this threshold have an elevated chemical activity (escape tendency) and redistribute to both extracellular plasma lipoproteins and intracellular organelles. The organelles make several homeostatic responses. They esterify active cholesterol for its storage and use it for the synthesis of side-chain oxysterols that then trigger pathways which reduce cholesterol accumulation. The active fraction also curtails cholesterol biosynthesis and ingestion and increases its export. In this way, the abundance of cholesterol is tightly coupled to that of its polar lipid partners through active cholesterol.

At least twice during the Neoproterozoic era (~635 and ~715 million years ago) there were strange and mysterious glaciations that differ dramatically from the recent (last few million years) glacial periods. For example, geological data suggests the entire ocean may have been covered with ice, which we call the ``Snowball Model!" At the same time, micropaleontological and molecular clock evidence indicates that photosynthetic eukaryotes thrived both before and immediately after these glaciations, which may suggest that some significant fraction of the ocean was ice-free (``Slushball Model"). We present a previously undescribed global climate state, the Jormungand state, that is nearly ice-covered with a narrow (~10-15 degrees of latitude) strip of open ocean near the equator. This state is sustained by internal dynamics of the hydrological cycle and the cryosphere. The Jormungand state is only possible if one accounts for the different albedo of bare and snow-covered sea ice, atmospheric dynamics, and the hydrological cycle. An important aspect of the Jormungand state is that there is a hysteritic bifurcation in global climate climate associated with it, which allows it to explain all of the geological evidence that a full Snowball model can explain, and separates it from the Slushball model.

We will start with a brief survey, covering the major scientific insights that led to the current discipline of "quantum information processing." We will discuss major promises (algorithmic speedup and information theoretic security) and outstanding challenges.

Then, we turn our attention away from any technological, funding, or citation concerns, and indulge in some fundamentally strange properties of quantum information and quantum correlations. For example, it takes infinitely many bits to describe a 2-level quantum state, but one can only extract one bit from it, and we will see the consequences of this disparity on cryptography, many body physics, and foundations of quantum mechanics. Given enough time, other examples (say, teleportation, entanglement, and channel capacities) will be discussed.

US power industry is facing a modernization stage that is usually referred to as transition to "smart" grid. In this talk I will review the key challenges that motivate this transition as well as the solutions proposed to address them. I will present a theoretical physicist view of the problem focusing on the analogies between power grid dynamics and other well-known statistical physical systems. Original results on decentralized control of reactive power flows and randomized scheduling of PHEV charging jobs will be discussed in the end of the talk.

Have you ever received a shock when you touched a doorknob after shuffling across a carpeted floor? The culprit, known as triboelectric charging, is also responsible for phenomena as innocuous as a rubbed balloon that makes your hair stand on end, or as dramatic as a lightning strike. While it is familiar to every child, fundamental understanding of triboelectric charging is so poor that even the most basic questions are still being debated, such as whether the transferred charge species are electrons or ions. Scientific progress is difficult because triboelectric charging is a non-equilibrium process (separated surfaces are neutral at equilibrium) that involves changes in electron states and occurs at a level of one electron per 100,000 surface atoms (physical and/or chemical defects at this low level likely control the behavior). This talk will describe our experimental and theoretical investigations of triboelectric charging, focusing on the charging that occurs in flowing granular materials.

Turbulent mixing and turbulent combustion are frontier issues that connect themes from mathematics, physics, computational science and engineering applications. Significant recent progress has largely resolved problems in one area of this topic, specifically the determination of the overall size of the turbulent mixing region in Rayleigh-Tauylor mixing. The mixing rate is summarized in a dimensionless coefficient alpha defined at the ratio of the mixing distance to an acceleration distance Agt^2, and is itself the subject of numerous controversies.

We will present results to determine alpha from simulation, often within two significant digits of the experimental values. A number of consensus views are challenged in the process, including the universality of alpha, the reliability of simulations not validated by experimental data, and the relative role of initial conditions in the observed experimental values for alpha.

We formulate a mathematical framework to better understand numerical convergence in the large eddy simulation (LES) regime. Validation, in a broader context, is supported by multiple applications for simulations of this nature, including turbulent combustion in the engine of a scram jet, chemical processing for nuclear fuel rod separation, primary breakup of a high speed jet of diesel fuel, and the design of targets for high energy accelerators.

Looking to the future, microscopic measures of mixing will be an important issue, either to specify a second moment of fluctuating quantities, or to supply a full probability density function (pdf).

Genetic circuits have been studied quite intensively in recent years. We have focused on oscillatory patterns in eucaryotic systems related to negative feed-back loops inside single cells. In many cases it is of interest to study how cells communicate with each other when cells are arranged in certain spatial structures, like biofilms and tissues. We have attacked this problem by means of a repressor-lattice where single repressilators (closed feed-back loops) are placed on a hexagonal lattice. Such systems can be build without any internal frustration and can in most cases exhibit stable, oscillating states. Commensurability effects however play a role and may lead to internal frustration causing breaking of symmetries and solutions of many different phases. Eventually, also chaotic solutions may be present. With bi-directed interactions the tissues locally exhibit switch-like behavior. During growth the tissues may develop 'defects' and we have found that mutations have a larger effect in such cases than in ordered tissues.

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.

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.

Using human evaluation of the happiness of words, we analyze a diverse set of large-scale texts which reflect cultural experience including 50 years of music lyrics, millions of weblogs, and billions of status updates from Twitter. We find that happiness rises and falls with age and distance from the Earth's equator; the 2008 Presidential Election was the happiest day in the blogosphere in the last 5 years; and the written form of the English language exhibits a pro-social bias. We also investigate how happiness is related to geospatial information, demographics, and network topology. What are the happiest cities? Which words anti-correlate with obesity? Does your happiness correlate with that of your friends? This talk will discuss the findings in the context of our ongoing effort in the Computational Story Lab at UVM to develop a remote sensor of population level happiness: the 'Hedonometer'.

The Runaway Greenhouse is a climate state in which the coexistence of a condensed reservoir of a greenhouse gas (such as a liquid water ocean) with a vapor phase in the atmosphere becomes impossible, resulting in all the condensed reservoir being converted to vapor, with attendant extreme increases in planetary temperature. This state occurs when the stellar radiation absorbed by the planet exceeds a certain threshold which depends primarily on the radiative properties of the gas in question and the surface gravity of the planet. The Runaway Greenhouse is believed to account for the present hot, dry state of Venus, and also defines the inner edge of the habitable zone about stars. In this talk I will discuss a number of recent results concerning the Runaway Greenhouse, including the role of subsaturation in permitting metastable non-runaway states, the vertical structure of runaway atmospheres about red dwarf stars, and some peculiarities of moist convection in a condensible pure water vapor atmosphere. I will also discuss the question of whether the Earth itself may be in a metastable non-runaway state, which would imply that it is conceivable that very extreme increases in atmospheric carbon dioxide could trigger a runaway.

Is the university as an institution under attack? To many working within academia it appears to be so. The pages of the Chronicle of Higher Education are full of anxious and angry debate about the ever rising cost of tuition, the increase in for-profit institutions, the undermining of professionalism coupled with the growing reliance on badly paid temporary adjuncts to make up for the loss of tenure track positions, and the kind of underfunding and neglect of State universities that is best represented by the problems besetting the University of California. On the other hand, a recent article by Forbes magazine listed “University Professor” as one of the least stressful jobs, and each year a new book appears in the bestseller lists that blames the failure of US universities – and in some cases the whole economy – on lazy professors who would rather carry out selfish and frivolous research than teach students what they need to be successful entrepreneurs. While agreeing that the university is in peril, the cause and solution seem to lead in quite different directions.

How can we make sense of this debate? Particularly when, to many whose working lives are based within universities, the systematic under-funding of universities and scientific research appears both illogical and unstoppable. In this talk I describe recent research undertaken in universities in Chile and the US that sheds light on how this situation came about, and the impact it has on the autonomy of individual scientific communities, and the relationship between scientists and society.

Signal or information processing and shaping of a response (a.k.a, signal transduction, regulation, sensing) is a common function performed by organisms on all levels of organization. In this talk, we will study information processing in cellular systems to answer questions like: What are the fundamental physical limits to the fidelity of information processing set by the intrinsic fluctuations in the cellular biochemical machinery? How close the cells come to these limits? What can they do to improve the performance? After introducing the general theoretical framework, we will address these and related questions in the specific experimental context of mammalian NF-kB signaling.

Probability does not exist. At least no more so than "mass" "spin" or "charm" exist. Yet probability forecasts are common, and there are fine reasons for deprecating point forecasts, as they suggest an unscientific certainty in exactly what the future holds. What roles do our physical understanding and laws of physics play in the construction of probability forecasts to support of decision making and science-based policy? Will probability forecasting more likely accelerate or retard the advancement of our scientific understanding? Model-based probability forecasts can vary significantly with alterations in the method of data assimilation, ensemble formation, ensemble interpretation, and forecast evaluation, not to mention questions of model structure, parameter selection and the details of the available forecast-outcome archive. The role of each of these aspects is considered, in the context of interpreting the forecast as a real world probability; the cases of weather forecasting, climate forecasting, and economic forecasting are contrasted. The notion of what makes a probability forecast "good" is discussed, distinguishing "skill" and "value".

For a probability forecast to be decision-relevant (as a probability forecast), it must be reasonably interpreted as a basis for rational action through the reflection of the probability of the outcomes forecast. This rather obvious sounding requirement proves to be the source of major discomfort as the distinct roles of uncertainty (imprecision) and error (structural mathematical "misspecification") are clarified. Probabilistic forecasts can be of value to decision makers even when it is irrational to interpret them as probability forecasts. A similar statement, of course, holds for point forecasts. In this context: do decision-relevant probability forecasts exist? And if not, how might today's forecasts be augmented?

Recent experimental evidence shows that the genetic networks of living organisms operate in a critical phase, namely, at the brink of a phase transition between ordered and chaotic dynamics. This has profound implications because it is precisely at the critical phase where robustness and evolvability, two central properties of living systems, can be understood within the same conceptual framework. However, the evolutionary mechanisms by which these networks became dynamically critical are still unknown. In this talk I will present an evolutionary model showing that dynamical criticality in genetic networks naturally emerges as a consequence of a delicate balance between two fundamental forces in evolution: the conservation of already acquired phenotypes (phenotypic robustness) and the generation of new ones (phenotypic innovation). We do so by evolving populations of random Boolean networks that can mutate and grow via gene duplication, and that are subjected to a Darwinian selection process that focuses on the conservation and innovation of the dynamical attractor landscape of the network population. Our results show that the trade-off between robustness and innovation suffices to make all the networks in the population evolve towards criticality. Furthermore, preliminary results indicate that the existence or absence of hubs (global regulators) similar to the ones observed in real genetic networks, is determined by the information content of the attractors through the evolutionary process.

President Obama’s May 2011 policy statement on "International Strategy for Cyberspace: Prosperity, Security, and Openness in a Networked World," lays out many of the principles for preventing harm and realizing the potential of this revolutionary technology. Yet, specific policy measures to ensure adequate cyber defenses in the private sector are not yet in place. Furthermore, the 2011 document fails to address adequately the uses of cyber operations by the United States in attacks on other countries' critical infrastructure. Revelations about the US deployment of malware in a cyber attack on Iran's nuclear centrifuges in 2009, and increased attention to the perils of damaging attacks on US financial, military, and infrastructure operating systems suggest the need for robust public policy recommendations and implementation. This talk will examine underlying assumptions and frameworks for policy development.

Certain freshwater fish from South America and Africa are able to sense their surroundings by emitting weak, millivolt-level electric discharges and analyzing the perturbations arising from nearby objects. This ability allows them to hunt, navigate, and communicate at night and in turbid waters. Weakly electric fish are able to localize targets in 3D space, assess target characteristics such as size, shape and electrical impedance, and recognize the sex, social status and perhaps individual identities of other fish. This talk will provide an overview of some of the key neural mechanisms and computational strategies involved in carrying out these challenging information processing tasks.

It is widely believed that synaptic modifications underlie learning and memory. This hypothesis has led to the study of many `learning rules' that implement in a simplified way how synaptic efficacy is controlled by neuronal activity. This talk will focus on a complementary research direction: investigating optimal storage properties in neural circuits. The first part of the talk will focus on the perceptron, the simplest feed-forward network model, as a simplified model of the granule-Purkinje cell pathway in the cerebellum. The distribution of synaptic weights of a perceptron that optimizes storage capacity can be computed using methods from statistical physics. This distribution has two striking features: (i) it contains a large number (at least 50%) of exactly zero weights (`silent' or `potential' synapses); (ii) positive weights are distributed according to a monotonically decreasing function. We find that the theoretical distribution fits closely the distribution of synaptic weights of connections between granule cells and Purkinje cells, suggesting Purkinje cells function close to their optimal capacity in adult rats, which we estimate to be about 5Kb per cell. In the second part of the talk, I will consider a network with a fully connected recurrent architecture, as a simplified model for local pyramidal cell networks of neocortex. In networks storing a large number of fixed point attractor states, the distribution of synaptic weights turns out to be exactly the same as the one for a perceptron, and hence contains a large fraction of `silent', or `potential' synapses. Finally, I will consider other statistical properties of the connectivity matrix (e.g.the joint distribution of synaptic weights for pairs of neurons), and compare the theoretical results with recently published data on synaptic connectivity in cortical slices.

Our Universe has a finite observable volume, and therefore within our Universe there is a unique most massive object. This object will be a cluster of galaxies. Computational and theoretical studies of the growth of structure have matured, and the mass of the most massive objects can now be robustly predicted to the level of a few percent. Furthermore, it is now possible to observe volume-limited samples of high-mass clusters. If objects are found with excessively large masses, or insufficient objects are found near the maximum expected mass, this would be a strong indication of the failure of our standard cosmological model. We show that preliminary observations are roughly consistent with expectations, with a few suggestive outliers.

At a time when microbial ecology is largely traveling along genomic roads, we cannot forget that the functions and services of microbes depend greatly on their behaviors, encounters, and interactions with their environment. New technologies, including microfluidics and high-speed video microscopy, provide a powerful opportunity to spy on the lives of microbes, directly observing their behaviors at the spatiotemporal resolution most relevant to their ecology, and enabling a deeper understanding of the biophysical mechanisms underpinning these behaviors. I will illustrate this 'quantitative natural history approach' to microbial ecology by focusing on marine bacteria, unveiling striking adaptations in their motility and chemotaxis and describing how these are connected to their incredibly dynamic, gradient-rich microenvironments. Specifically, I will present (i) sub-micrometer imaging of single cells at up to thousand frames per second, demonstrating that marine bacteria have a unique mode of swimming, exploiting a mechanical buckling instability of their flagellum to reorient; and (ii) microfluidic experiments that capture the dramatic chemotactic abilities of marine bacteria, including bacterial pathogens storming towards the roiling surface of their coral hosts. Through these examples, I aim to illustrate how we can use direct visualization to learn about the biophysical mechanisms and the ecological implications of the behaviors of the smallest of life forms.

I will begin by discussing experiments in which we observe the emergence of localized, crumpled features from smoothly deformed sheets. I will then move on to describe the 3-dimensional spatial structure of highly crushed elastic and plastic sheets. One of the objectives of our experiments is to understand the effect of the protocol and boundaries on the crumpling process. We follow the development of stress-focused structures as well as the emergent organization of structural elements, such as the condensation of planar facets. I will end by discussing the evidence for an ordered state underlying the complex, seemingly-disordered geometry of a crumpled object.

By decreasing the temperature the relaxation time of super-cooled liquids increases by more than ten orders of magnitude. This feature, which is the hallmark of the glass transition, is also the main obstacle to study it because liquids inevitably fall out of equilibrium before showing a genuine critical behavior. In this talk I propose a way to short-circuit this problem, cross the phase transition and sample the ideal glass in equilibrium. It is based on the idea of pinning particles at random from an equilibrium configuration. Contrary to cooling protocols, immediately after pinning the remaining free particles are automatically in equilibrium. Thus, the ideal glass can be reached easily: one has just to pin enough particles. This makes possible a whole new set of investigations, in particular studying the glass transition approaching it from both sides. I will present the theory of the glass transitions induced by random pinning, discuss generalizations of the pinning procedure and differences with other approaches recently presented in the literature.

Dynamical systems have a natural tendency to relax through dissipative processes to a minimum-energy state, subject to any relevant constraints. An example is provided by the relaxation of a magnetic field in a perfectly conducting but viscous fluid, subject to the constraint that the magnetic field lines are frozen in the fluid. One may infer the existence of magnetostatic equilibria (and analogous steady Euler flows) of arbitrary field-line topology. In general, discontinuities (current sheets) appear during this relaxation process, and this is where reconnection of field-lines (with associated change of topology) can occur. Slow change of boundary conditions can lead to critical conditions in which such topological jumps are inevitable.

A simple example of this type of behaviour that can be realised in the laboratory is provided by a soap-film bounded by a flexible wire (or wires) which can be continuously and slowly deformed. At each instant the soap-film is relaxed in quasi-static manner to a minimum-area (i.e. minimum-energy) state compatible with the boundary configuration. This can however pass through a critical configuration at which a topological jump is inevitable. We have studied an interesting example of this behaviour: the jump of a one-sided (Möbius strip) soap-film to a two-sided film as the boundary is unfolded and untwisted from the double cover of a circle. The nature of this jump will be demonstrated and explained.

Random Matrix Theory was initially developed to explain the eigen-energy distribution of heavy nuclei. It has become clear by now that its domain of application is much broader and extends to very different fields such as number theory and quantum chaos, just to cite a few. In particular, it has been conjectured—and proved or verified in some special cases—that quantum ergodic (or chaotic) systems are characterized by eigen-energies statistics in the same universality class of random matrices and by eigen-functions that are delocalized over the configuration space. On the contrary, non-ergodic quantum systems, such as integrable models, are expected to display a Poisson statistics of energy levels and localized wave-functions. Starting from Anderson’s pioneering papers, similar properties have also been studied for electrons hopping in a disordered environment. Remarkably, also in this case, similar features of the energy-level statistics have been found. All that has lead to the conjecture that delocalization in configuration space, ergodicity and level statistics are intertwined properties.

In this talk we revisit the old problem of non-interacting electrons hopping on a Bethe lattice with on-site disorder. By using numerical simulations, the cavity method and mapping to directed polymers in random media we unveil the existence of an intermediate phase in which wave-functions are delocalized but the energy-level statistics is Poisson. This new phase, in which the system is non-ergodic but delocalized, may play an important role in several fields from random matrix theory to strongly interacting quantum disordered systems, in particular it could be related to the non-ergodic metallic phase conjectured to exist in the context of Many-Body Localization.

We generate nematic droplets with handles and stabilize them against surface-tension instabilities using yield-stress fluids. For toroidal droplets, the nematic spontaneously twists; this happens for all, slender and fat tori, as a result of saddle-splay contributions to the elastic free energy. The addition of handles is accompanied by the presence of defects in the order. We find there are two -1 defects per handle, located in regions with saddle geometry.

Properties of matter not adequately described by classical physics have gained a lot of attention in quantum information science and condensed matter physics. The non-classcality is mostly attributed to "entanglement", which can be utilized for quantum computing and yet makes the study of quantum matter on classical computers so difficult.

In this talk we first discuss the ground state properties of quantum spin chains and trees with generic local interactions within the framework of Matrix Product States formulation. We then present the first example of a Frustration Free translation-invariant spin-1 chain that has a unique highly entangled ground state and exhibits some signatures of a critical behavior. The mathematical techniques used here may be of independent interest.

The process of diffusion is a consequence of particle number conservation and locality, in systems with sufficient damping. Diffusive processes are ubiquitous in nature — familiar examples range from pollen grains executing Brownian motion in water, to electrical charge transport through a power line. Yet fundamental questions remain to be addressed in the quantum mechanical formalisms leading to diffusion from a microscopic theory. In this talk I shall first elucidate the standard field theoretical technique for deriving the law of diffusion for electrons in a crystal, in the presence of disorder. Through this example, I shall also introduce our new analytical tools for addressing anisotropic scattering, thus deriving the Boltzmann diffusion constant via the diagrammatic approach. Next I shall introduce Weyl semimetals, an exotic material with topologically protected gapless surface states with discontinuous Fermi surfaces, arising from the valence and conduction bands touching in three dimensions. The derivation of the correct diffusion law for this material using the previously introduced techniques will then be outlined. I shall conclude by showing how this is a diffusive process with a nontrivial memory function and discussing the experimental consequences of this result.

Flow through nanometer-scale pores is important in biology, geological flows through porous rocks, and in filtration and separation processes. Flow through these pores is controlled by different physics than conventional macroscopic pipes. Single phase fluid flow in nanometer channels is extremely sensitive to slip and the exact boundary conditions at the solid- liquid interface. Because curvature of interfaces in small channels is very high, two phase flows are subject to large Laplace pressures and are sensitive to the contact angle and the wetting properties of the interface. Experiments by others on flow through “carpets” of carbon nanotubes have yielded flow rates that are hundreds of times greater than predicted by conventional hydrodynamics. I will discuss recent experiments in our lab on pressure driven flow through single nanopipes using water, nitrogen and helium (including superfluid) over a wide range of temperature. The results show clear transitions between distinct flow regimes. I will also discuss contact angle measurements of water on graphite. Somewhat paradoxically, water does not wet many materials. Our experiments have identified the first wetting transition in water at T=280C.

Drop coalescence has been thoroughly studied, especially for two liquid drops coalescing in vacuum or air. However, little is known about how the surrounding fluid influences the process when the two drops are surrounded by an external fluid with significant density or dynamic viscosity. This two-fluid coalescence is the important situation that appears commonly in nature and industry. We use a combination of high-speed imaging and an ultrafast electrical method to study coalescence in this regime. We find that even if the outer fluid is 50 times more viscous than the drops, the coalescence speed need not be affected, even at the earliest moments. To understand the behavior of the outer fluid in isolation, we turn to air bubbles coalescing inside a very viscous external liquid. Our data is consistent with a simple ansatz that the length-scale for the flows is much larger in the outer fluid than in the drops, so that viscous stresses in the drops will always dominate at the beginning. This leaves us with the parting lesson: “it’s what’s inside that counts”.

While the concept of evolution as mechanism for iterative improvement has existed for centuries, three key developments in the past 20 years have made it promising framework for science and engineering in the 21st century. First, artificial variants of evolution, specifically those implemented through computer algorithms, have successfully transformed the biological concept into a robust and efficacious optimization method. Second, computer simulations of a variety of physical systems are now fast enough to be effectively used to compare the relative quality of a potential design against a small population of alternatives. Third, advances in rapid prototyping, such as 3D printing, present a means to physically realize complicated or unconventional designs that may result from unconstrained evolution in a digital environment.

In this talk, I will discuss examples of how these three developments may be synthesized to address particular problems in granular physics. First, I will show how artificial evolution can be used with simulations and 3D printing to explore the role of particle shape in granular materials. This approach can be used to discover new, unexpected particles that form the stiffest packings, softest packings, and even exotic configurations that stiffen, rather than weaken, under compression. Furthermore, experiments on 3D printed versions of digitally designed particles directly validate these results.

Outside of mechanical response, I will present results about shapes that pack densest when poured into a container. In this case, I will show how artificial evolution can be used to not only identify particularly optimal shapes, but also to explore the role of physical variables, like friction, or the packing procedure itself.

Finally, I will show a variation on these themes that performs evolution directly in the lab by leveraging the jamming concept to rapidly prototype experiments. In this case, a fully automated experiment adjusts whether patches of material are liquid-like or solid-like to discover configurations that, when loaded at one side, transmit the lowest force to the other. In spite of a search space of roughly 2^36 candidates, evolutionary algorithms are able to find a particularly novel solution in just under 12 hours.

In the 1970’s our low temperature research group was drawn into a new line of research concerning the odor from a Springfield paper plant operated by the Weyerhauser company. It occurred to me that passing the flue gases through a cold trap would likely solve the problem. We sought out the management, who were quite receptive to the idea of a cold trap, and supported research which proved to be quite effective. Based on this experience, we applied to NSF for a study of trapping SO2 from coal plants and published a paper on the laboratory results. We also engaged the Bechtel Power Company to do an engineering study of the possibilities for a major coal plant. One problem we encountered was the simultaneous production of CO2, which at the time was not considered to be as important as it is today. This talk will discuss the possibilities, thermodynamics, and added costs of capturing CO2 cryogenically, as an example of how physics can be applied to urgent world-wide problems.

A drop impacting a solid surface with sufficient velocity will splash and emit many small droplets. Surprisingly, however, removing the ambient air suppresses splashing completely. There are several distinct regimes of splashing that all display this extreme sensitivity to gas pressure. In particular, decreasing the air pressure also eliminates splashing on a rough surface even though the overall form of the splash is significantly different in this regime. The mechanism underlying how the surrounding gas affects splashing remains unknown. Our approach to unveil this mystery is twofold. (i) We establish a unique criterion that predicts the transition from smooth deposition to splashing, taking into account all the relevant liquid and gas properties. (ii) We search for where on the drop surface the air matters. We look closely below the drop, at the air flow above the drop and at the moving contact line near the drop edge.

What can one uncover by simply watching a bacterial cell grow and divide, over and over again? It turns out, a lot! Evidently, one learns how the size of each cell increases with time. More interestingly, one finds the nature of the nuanced interplay between biological length scales and time scales, which determines when the size of a cell is just right for it to divide. Further, one could even discover that there is but one primary time scale, a cellular ``unit of time'', which governs the nature of fluctuations in both growth and division, and thus make nontrivial predictions for how these fluctuations must scale when ambient conditions are changed. Finally, one could ask how all of this is revised when the cell is forced to senesce (``age'') by being subjected to inclement nutrient conditions. In this talk I shall first introduce the experimental technology that we have developed, which allows for probing such issues, and then discuss some of our surprising findings.

The dynamics of how two rough frictional interfaces detach is a fundamental question in fields ranging from material science to geophysics. On the one hand, the onset of frictional motion is thought to be characterized by the static friction coefficient that couples two materials. For hundreds of years, this has been considered to be a material constant. On the other hand, the same processes that give rise to the onset of frictional motion also cause earthquakes, when tectonic plates locked together by friction start to slip. The frictional interface that locks two macroscopic blocks of material together composed of an ensemble of discrete microscopic contacts that give the interface its strength. We will present new experiments that show how the onset of frictional motion is caused by the fracture of these contacts. This takes place via rapid earthquake-like rupture processes that immediately precede the onset of macroscopic motion that we know as frictional sliding. We will show that both a number of different modes of earthquakes exist and that the “static friction coefficient” is not a material constant at all, but is intimately related to the details of how forces are applied to a system. We will present new results that describe the detailed spatio-temporal processes that take place within a rough and dry frictional interface.