Due to cancelled travel plans, this talk has been postponed until March 12th.

According to holographic duality, turbulent fluid flows encode the evolution of certain black holes in one higher spacetime dimension. Holographic duality can thus be exploited to gain insight into the evolution of black holes from our understanding of turbulence and vice versa. I will discuss both normal and superfluid turbulence and their dual gravitational description. I will argue that the Kolmogorov scaling observed in normal turbulence implies that dual black holes have a fractal-like structure. Likewise, based on the evolution of black holes I will demonstrate that two dimensional superfluid turbulence enjoys a direct energy cascade to the UV. This later observation stands in stark contrast to normal fluids in two dimensions, where enstrophy conservation implies an inverse energy cascade to the IR.

This being a seminar series dedicated to computations, I'll try to communicate the difficulties we have encountered in recent times when attempting to pinpoint the origin of several anomalies affecting dark matter searches, possible hints of detection. These include systematics affecting the operation of the detectors and our knowledge of their response to low-energy nuclear recoils, astrophysical uncertainties, and the broad range of particle couplings that could mediate the interaction of a Weakly Interacting Massive Particle with the target. Perhaps a bit too much to compute.

The deceptively simple-looking problem of advection-diffusion by a smooth time-dependent flow has a very rich phenomenology and poses, in a simpler context, many of the same challenges as turbulence. Over the past two decades, investigators at the University of Chicago have contributed greatly to the understanding of this problem and its variants -- a process of which I have been privileged to be a part. In his recent Amick Lectures, Peter Constantin summarized a number of rigorous theorems providing a foundation for the subject. In this lecture I will survey the phenomenology and some of its applications. Topics to be discussed include strange eigenmodes, ergodicity, and connections to Julia set problems. Extensions beyond advection-diffusion of a passive tracer, for which the passive advection-diffusion problem provides a launching point, include surface quasi-geostrophic turbulence, advection-diffusion-condensation, and advection-diffusion-reaction (with applications to flame quenching in the generalized KPP problem).

The coupling of domain walls to gravity leads to a set of questions closely connected to the study of electromagnetism in one spatial dimension. I will discuss the construction of a particularly nice class of domain walls in string theory. The construction suggests a holographic structure that can accommodate accelerating universes.

A seminal set of experiments on continuously sheared granular media reveals vortex-like structures with short lifetime and significant intensity. In classical fluids, vortices have long been known to significantly enhance heat transfer via convective internal mixing, but in engineering and geophysical analyses of heat flow through granular media this has been continuously neglected. Computer simulations that capture the vortices in the granular media unravel astonishing convective heat fluxes, which challenge the previous paradigm, and inspire new technologies.

Bacterial infection is characterized by a multi-scale noisy dynamics with unpredictable outcome. Quantitative understanding of these processes is limited in no small part due to the lack of clear experimental data. In my talk I introduce bacterial infection of the worm intestine as a minimal tractable model of bacterial infection. By thinking about infection as an ensemble of emergent phenomena, we show how collective behavior of bacterial population drive the progression of infection, and how worms act collectively to avoid it.

Ten years ago, U.S. natural gas cost 50% more than that from Russia. Now it is three times less. U.S. gas prices plummeted because of the shale gas revolution. But a key question remains: At what rate will the new hydrofractured horizontal wells in shales continue to produce gas? The problem seems extremely complicated, but it has a surprisingly simple and accurate answer in terms of a scaling function. I will discuss some of the previous cases in which scaling functions have given unreasonably simple solutions, and show that in this instance a single curve matches well the gas production from thousands of wells in Texas' oldest gas play, the Barnett Shale.

Photosynthesis, the process by which energy from sunlight drives cellular metabolism, relies on a unique organization of light-harvesting and reaction center complexes. Recently, the organization of light-harvesting LH2 complexes and dimeric reaction center-light harvesting I-PufX (RC- LH1-PufX) core complexes in membranes of purple non-sulfur bacteria was revealed by atomic force microscopy (AFM). Here, we discuss optimal exciton transfer in a biomimetic system closely modeled on the the structure of LH2 and its organization within the membrane using a Markovian quantum model with dissipation and trapping added phenomenologically. In a deliberate manner, we neglect the high level detail of the bacterial light harvesting complex and its interaction with the phonon bath in order to elucidate a set of design principles that may be incorporated in artificial pigment-scaffold constructs in a supramolecular assembly. We show that our scheme reproduces many of the most salient features found in their natural counterpart and may be largely explained by simple electrostatic considerations. Most importantly, we show that quantum effects act primarily to enforce robustness with respect to spatial and spectral disorder between and within complexes. The implications of such an arrangement are discussed in the context of biomimetic photosynthetic analogs capable of transferring energy efficiently across tens to hundreds of nanometers. We also present experimental results obtained using two-dimensional photon echo spectroscopy that reveal complex quantum dynamics in isolated LH2 complexes.

Liquids and solids tend to stick to each other. When a liquid droplet sticks to a solid surface we call it wetting. When a solid particle sticks to a solid surface we call it adhesion. The classic coarse-grained descriptions of these two phenomena are quite distinct from each other. Both descriptions assume that solid objects undergo very little deformation during wetting and adhesion. In this talk, I will show how this assumption breaks down when the solids are soft enough and how wetting and adhesion really are not that different after all.

There is a deep analogy between the physics of crystalline solids and the behavior of superfluids, dating back to pioneering work of Philip Anderson, Paul Martin and others. The stiffness to shear deformations in a periodic crystal resembles the superfluid density that controls the behavior of supercurrents in neutral superfluids such as He4. Dislocations in solids have a close analogy with quantized vortices in superfluids. Remarkable recent experiments on the way rod-shaped bacteria elongate their cell walls have focused attention on the dynamics and interactions of point-like dislocation defects in a cylindrical crystalline shell. In this lecture, we review the physics of superfluid helium films on cylinders and discuss how confinement in one direction affects vortex interactions with supercurrents. Although there are similarities with the way dislocations respond to strains on cylinders, important differences emerge, due to the vector nature of the topological charges characterizing the dislocations.

Biological organisms in the real world do not typically grow up in well-mixed test tubes or featureless Petri dishes, but instead must find ways to prosper in the presence of environmental inhomogeneities that vary in space. In experiments carried out by Wolfram Moebius, we have created a spatially random bacterial lawn on a Petri dish, with two fluorescently labelled E. coli strains, one which is highly susceptible to phage T7, and one which is not. Dark viral plaques due to T7 infect and expand through a mottled environment, sometimes tunneling through barriers provided by the less susceptible species. We have also developed the capability to print bacterial lawns in prescribed patterns. Such experiments, when combined with a theory of the nonequilibrium statistical dynamics of viral diffusion, mutation, genetic drift and selective advantage, have considerable potential for understanding the spread of viral epidemics, the effect of spatial bottlenecks on evolution, etc. By probing multicolored bacterial range expansions around nutrient-free obstacles, we also study the effect of spatial inhomogeneities on genetic demixing.

Microorganisms living in the ocean can be subject to strong turbulence, with cell division times in the middle of a Kolmogorov-like cascade of eddy turnover times. We explore the dynamics of a Fisher equation describing cell proliferation in one and two dimensions, as well as turbulent advection and diffusion. Because of inertial effects and cell buoyancy, we argue that the effective advecting velocity field is compressible. For strong enough compressible turbulence, microorganisms such as bacteria and phytoplankton track, in a quasilocalized fashion, sinks in the turbulent field, with important consequences for the carrying capacity and for fixation times when two genetically different species compete.

A sheet of paper that has been crumpled and flattened retains some amount of shapability that a bare, uncrumpled, sheet does not have: when deformed by external forces, it retains the deformed shape after the forces are removed. Using a frustrated two dimensional lattice of springs, we show that such shapability can be attained in a non-dissipative system. Numerical investigations suggest an extensive number of bistable energy minima using several variants of this scheme. The numerical sheet can be bent into a nearly-closed cylinder that holds its shape. We verify that the deformed shape is locally stable and compare its bending modulus in the deformed state with that in the initial flat state. We investigate the threshold for non-elastic deformation using various kinds of forcing.

The speed of a Rayleigh-Taylor unstable, premixed flame could plausibly be influenced by both the Rayleigh-Taylor instability of the flame front and the turbulence generated by the flame itself. Both of these mechanisms stretch and wrinkle the flame front, increasing its surface area and speed. But which of these two processes is dominant? Is the flame speed better modeled by the Rayleigh-Taylor speed or the root-mean-square velocity of the turbulence? To address these questions, I will present three-dimensional, direct numerical simulations of Rayleigh-Taylor unstable flames that generate moderately turbulent conditions and discuss the influence of the Rayleigh-Taylor instability and turbulence on the flame front.

Tessellated patterns, realistic animals, and curved polygonal shapes are all examples of the beautiful and amazing sculptures that can now be made using Origami, the art of paper folding. This art form has experienced tremendous growth with the advent of mathematical techniques that allow the basic structure of any new sculpture to be plotted out before any folding occurs, and laser cutter technologies that have made it easier to create folds in a variety of materials. In addition to their static properties, Origami sculptures can be designed to have a wide variety of mechanical properties making them responsive and tunable. Here, I will present a work-flow pipeline for materials design that uses Origami as a means of devising basic modular building blocks that can be assembled into larger-scale mechanical meta-materials. We start by working with origami artists to identify and generate candidate folding patterns for study. Next, we develop full-scale models using laser cut Mylar and paper sheets for rapid design, testing, and redesign. Mechanical measurements of these prototypes are combined with numerical simulations to identify the key relations between mechanical properties and geometric structure that give rise to the measured properties. Once a desirable pattern is identified, it is scaled down to a sub-mm tri-layer temperature-responsive polymer sheet using photolithographic techniques. The polymer sheet is capable of folding and unfolding as a function of temperature, and moreover, exhibits similar geometry-driven mechanical properties as the bench top prototypes. Stepping-back, we see this work-flow from design to synthesis as a conceptual tool that will help expedite origami-inspired materials.

Many phenomena are well-described, qualitatively and quantitatively, by macroscopic approaches, but some of those descriptions lose their validity when we try to apply them to small systems. The example that brought us to this issue was the breakdown of the Gibbs Phase Rule for small clusters of atoms or molecules; simulations and then experiments showed that atomic clusters could exhibit solid and liquid forms to exist in dynamic equilibrium over ranges of temperature and pressure, rather than just at a single temperature for each pressure. This particular breakdown is easy to understand when viewed in "the right" way, and is in fact completely consistent with traditional thermodynamics. It turns out to be possible to find the approximate upper limit of size for which the violation of the Phase Rule would be observable. This approach can now be generalized to enable us to understand the "boundary" below which a chosen property is no longer well-described by its macro approach. One well-studied example is the metal-insulator transition in metal clusters. Others that pose major challenges include determining the system size above which properties vary monotonically with the number of elements, and, similarly, determining the size above which the system exhibits the bulk structure as its most stable state. An interesting challenge is finding phenomena to add to this list.

As part of its mission, the Panel on Public Affairs (POPA) of the American Physical Society semi-regularly develops statements for the APS on matters of public interest. One such matter is climate change, and over the past 6 months, POPA has been involved in a re-examination of the existing APS statement on climate change. I will discuss our approach, focusing on the dual issues of what we as physicists can say about this topic with some assurance, especially in the realm of prediction - and how do we explain this to a public that is highly polarized on this subject, not tolerant of nuance, and poorly educated on risk assessment and risk tolerance. All of these issues relate closely to how physicists deal with uncertainty quantification of models, and how these may translate - or not - to modeling in the social sciences.

Ice streams are concentrated regions of fast flow within continent-scale ice sheets that can account for over 90% of an ice sheet’s internal mass transport. Ice stream flow exhibits variability at a range of temporal scales, with variability at hundred- to thousand-year time scales having a significant influence on net ice sheet mass balance, and as a result, global sea level. A dynamical systems approach is adopted to analyze a simplified box model of ice stream flow and hydrology. Within a range of parameters relevant to modern West Antarctica, there lies a subcritical Hopf bifurcation between stable ice streaming and oscillatory ice stream behavior. The associated hysteresis in ice stream behavior has implications for the response of ice streams to climate change. Combining these ice stream physics with a one-dimensional ice flow model produces shock-like “activation waves”. The associated oscillations in grounding line position complicate canonical grounding line stability theory and the idea of a vulnerable West Antarctic Ice Sheet.

Anyone who has played with sand has noticed the peculiar characteristic of this material; it can behave like a fluid but also behave like a solid. It is this duality that makes granular materials so interesting and yet so challenging to understand and predict. In addition to enabling both existence and failure of sand castles, granular materials and their suspension in liquids are prevalent in a wide range of natural and man-made processes. These include the industrial handling of seeds and slurries, clogging of drilling wells, and geological phenomena such as landslides and debris flows. However, most of our understanding of how these materials flow is based on empirical observations because of the complexity of having more than one phase (the solid and the fluid one), hampering, for example, the design of efficient transport of a suspension of solids in a fluid medium. The goal of my research is therefore to help develop constitutive models that predict how granular materials behave when sheared as a function of physical parameters, using carefully controlled experiments to validate and refine such models. My current research focuses on liquid-solid mixtures, and unlike the mechanics of dry granular material flows which are dominated by collisions and friction, the mechanics for these mixtures involve the interaction between the solid particles, the inertial effects from both liquid and solid phase, and viscous effects of the liquid. The experiments use a specially designed Couette cylindrical rheometer that allows probing the transition from transporting a pure liquid to transporting a dense suspension of particles. In particular, I will discuss the effects of particle concentration and the density ratio between the 2 phases under shear conditions where particle collisions might become important.

Biology builds many structures in a bottom-up manner: locally interacting degrees of freedom are programmed to produce a desired global behavior. For example, proteins self-assemble into macromolecular complexes; RNA and protein polymers fold into 3-d structures; membranes with locally varying growth rates fold into structures during development of organisms. Such biological materials are often highly heterogeneous — the number of kinds of degrees of freedom (for e.g, number of particle species) is large and comparable to the system size. Recent methods of materials science have emulated these examples and raised questions about the limits and possibilities of this bottom-up framework.

I will discuss two novel phenomena unique to heterogeneous materials synthesis : 1. the benefits of aiming 'off-target' using the control parameters of synthesis (e.g., concentrations, binding energies) 2. a 'parameter demixing’ property of disordered heterogeneous systems that enables simple design of multi-potent materials that can respond to the environment.

One of the hallmarks of living systems is self-replication. Mimicking nature’s ability to self-replicate would not only give more insight into biological mechanisms of self-replication but also could potentially revolutionize material science and nanotechnology. Over the past sixty years, much research, both theoretical and experimental, has been focused on understanding and realizing self replicating systems. However, artificial systems that efficiently self-replicate remained elusive. In this talk I will discuss schemes for self-replication of small clusters of isotropic particles. By manipulating the energy landscape of the process I show how exponential replication can be achieved. As a proof of principle, I will also show exponential self-replication of an octahedral cluster using finite temperature computer simulations.

Materials capable of undergoing large deformations like elastomers and gels are ubiquitous in daily life and nature. An exciting field of engineering is emerging that uses these compliant materials to design active structures and devices, such as actuators, adaptive optical systems and self-regulating fluidics. Compliant structures may significantly change their architecture in response to diverse stimuli. When excessive deformation is applied, they may eventually become unstable. Traditionally, mechanical instabilities have been viewed as an inconvenience, with research focusing on how to avoid them. Here, I will demonstrate that these instabilities can be exploited to design materials with novel, switchable functionalities. The abrupt changes introduced into the architecture of soft structure by instabilities will be used to change their shape in a sudden, but controlled manner. Possible and exciting applications include materials with unusual properties such negative Poisson’s ratio, phononic crystals with tunable low-frequency acoustic band gaps and reversible encapsulation systems.

“With four parameters I can fit an elephant; with five I can make it wag its tail.” Systems biology models of the cell have an enormous number of reactions between proteins, RNA, and DNA whose rates (parameters) are hard to measure. Models of climate change, ecosystems, and macroeconomics also have parameters that are hard or impossible to measure directly. If we fit these unknown parameters, fiddling with them until they agree with past experiments, how much can we trust their predictions? Multiparameter fits are sloppy; the parameters can vary over enormous ranges and still agree with past experiments. Nonetheless, they can often make useful predictions about future experiments, even allowing for these huge parameter uncertainties: a few stiff combinations of parameters govern the behavior. These sloppy models all appear strikingly similar to one another – for example, the stiffnesses in every case we’ve studied are spread roughly uniformly over a range of over a million. We will use ideas and methods from differential geometry to explain what sloppiness is and why it happens so often. Finally, we shall show that models in physics are also sloppy – that sloppiness is a kind of parameter compression which makes science possible, both in physics and in other fields.

The Kepler mission represents a breakthrough in the dynamics of planetary systems. The number of systems with detectably perturbed orbits jumped from two to over a hundred. But the interpretation of these perturbations has lagged the collection of data. I am modeling the systems with high signal-to-noise transit timing variations (TTVs), which have distinctive features beyond parabolas or sine curves. Such features can uniquely determine the mass and orbital parameters of the perturbing planet. In a few systems of multi-transiting planets, I infer the presence of a planet that does not transit. The future transit times of some systems with particularly large TTVs are starting to become uncertain, which I quantify with a Monte Carlo sampling of our dynamical fits. For these systems we are scheduling and obtaining new transit observations, both from the ground and from space observatories, lest we lose knowledge of when to look for transits. With continued monitoring, the TTVs in these systems will result in mass-radius measurements for cool exoplanets and inferences on the formation and evolution of exoplanetary systems.

Discrete scaling symmetry, shown in Russian nesting dolls and in the self-similar structure of snow flakes, displays a unique form of beauty in art and in nature. In quantum world, the discrete scaling symmetry is rare and implies a long-range correlations resulting in a log-periodic behavior in their observables.

Vitaly Efimov predicted in 1970 that a universal set of three-body bound states with the scaling symmetry emerges when the pair-wise interactions are resonantly enhanced. The prediction has stimulated wide range of interest in nuclear, atomic, high-energy and chemical physics. In recent years, Efimov states have been identified in a number of cold atom systems.

In this talk, we report the observation of three consecutive Efimov trimer states in a Fermi-Bose 6Li-133Cs mixture. The states are revealed from the resonance structure in the three-body loss spectrum. The resonance positions follow closely a geometric progression and provide a model-free confirmation of the discrete scaling symmetry.

The transport of interacting particles in confining geometries is of fundamental interest. At the macroscopic scale, systems such as colloids in a tube, grains in a silo and pedestrians in a corridor exhibit dynamical phenomena such as pinning, jamming and layering as they move through constrictions. At the microscopic scale, confinement of electrons in quantum point contacts gives rise to the quantization of electrical conductance, an effect that can be modified significantly by electron-electron interactions. Here we present transport measurements of electrons in split-gate devices, in which the electrons behave as classical, rather than quantum, particles. Our experiments allow us to investigate fundamental processes governing the transport of interacting particles through bottlenecks, and study the influence of confinement on phase transitions. Electrons trapped in surface states above a liquid helium surface form an ideal classical electron system, due to the inherently low electron density and the weakly screened Coulomb interaction between particles. By confining the liquid helium substrate in microscopic channels, and further tuning the effective channel width using gate electrodes, electron transport in quasi-one-dimensional (Q1D) confinement can be investigated. We demonstrate that the conductance through point contact-like constrictions increases in a series of steps as the channel opens, not due to quantum mechanical effects, but due to the increasing number of electron rows able to pass through the constriction[1]. At low temperatures, when the electron system forms a Wigner crystal, more complex transport mechanisms are observed in which the commensurability of the electron lattice with the saddle-point confinement influences the rate of particle flow[2]. We also investigate the melting of Wigner crystals in uniform Q1D confinement, and find that the melting of the system depends on the number of electron rows and the strength of the confinement, as well as the temperature[3]. Furthermore, we demonstrate the electrostatic control of a single chain of electrons, several hundred particles in length. Such a system may be of use in future quantum information processing schemes in which the motional or spin states of electrons can be used as qubit basis states[4].

For this talk two problems that involve thin lm formation in Hele-Shaw cells will be discussed. First, pulsatile air flow is used to displace a nite volume of viscoelastic liquid. Experiments are performed using a radial Hele-Shaw cell at gap spacings rang- ing from 50-200 microns. The viscoelastic liquids are a mineral oil mixed with high molecular weight poly-isobutylene (M.W. 4.7 106 g/mol at concentrations 0.01-0.1% by weight) and an aqueous solution containing poly-acrylamide (M.W. 5-6 106 g/mol at concentrations 0.1-0.5% by weight). Maximum air injection pressures range from 0.1-0.5 psig, and pulsed (square wave) injection frequencies range from 0.1-10 Hz. Data for the residual film thickness, stable area expansion and gas area expansion rate will be presented. Second, the downward vertical displacement of an air-liquid meniscus in a two-dimensional Hele-Shaw cell is studied. Subsequently, a thin film is deposited on the substrate walls and then it drains leading to rupture. Experiments are performed using silicone oil while varying the initial displacement height of the meniscus before descent, and the Hele-Shaw cell gap spacing. Theoretical analysis is also performed for the two dimensional drainage flow of the thin film that forms. Thin film equations are analyzed and computed for the problem using a non-stationary boundary condition that is required to satisfy zero flux at the inlet. The spatial derivatives are discretized using 4th order finite difference while the time is advanced using an adaptive Runge- Kutta method.

Dimensional Analysis is a remarkable tool in that it can be used in almost any context in the sciences. It can give you a hint to the solution of a non-linear partial differential equation or it can lead to a universal function describing a whole class of materials. This talk will be an introduction to dimensional analysis and similarity solutions. I hope to end this talk with a bang!

One of the most basic but intriguing properties of quantum systems is their ability to `tunnel' between configurations which are classically disconnected. That is, processes which are classically impossible are allowed by quantum tunneling. In this talk I will outline a new, first-principles approach combining the semi-classical approximation with the concepts of post-selection and weak measurement. Its main virtue is to provide a real-time description within which sharp answers can be given to questions such as 'how long did the tunneling take' and 'where was the particle while it was tunneling?' Potential applications span a vast range, from laboratory tests to black holes and cosmology.

What do cornstarch suspensions, glacial ice mélanges, and coin dozers have in common? They all show dynamic jamming fronts when being perturbed while their packing fraction is close to the jamming point. In this talk I will show results from a number of 2D systems, where we can directly observe the response to a localized perturbation. Using high speed imaging of a floating layer of cornstarch suspension, I will show that humans can run on an infinitely deep pool of cornstarch suspension, much like how the green basilisk lizard (a.k.a. the Jesus lizard) is able to run on water, i.e. purely by momentum transfer, but without having to be as fast and smart as the lizard. The very same force that allows us to run on cornstarch suspensions is providing a resisting force to calving icebergs, which I will show through the analysis of radar images taken at the glacier terminal at Jakobshavn, Greenland. As it turns out, jamming fronts are everywhere and can be found on many scales. All it takes is a collection of particles that are close to each other, but not quite jammed (yet).

In this talk, I will discuss a few laboratory experiments that were inspired from examples of biological locomotion. There, solid structures were forced to interact with their surrounding fluid. These structures, or dynamic boundaries, interact with fluid in asymmetric fashions - either because of their anisotropic geometry or by the spontaneous breaking of symmetry in their response to the fluid. When subject to reciprocal forcing, the coupled systems behave in ways that can be described as ratchets. The emerging motion of the fluid or structures may help us to better understand many types of locomotion in the biological world.

Moving through a densely-populated environment can be surprisingly hard, owing to the problem of congestion. Learning to deal with congestion in crowds and in networks is a long-standing and urgently-studied problem, one that can be equally well described at the level of dense, correlated matter or at the level of game-theoretical decision making.

In this talk I describe two related problems associated with human motion planning. In the first part I consider a description of pedestrian crowds as densely-packed repulsive particles, and I address the question: what is the form of the pedestrian-pedestrian interaction law? Starting with real-life crowd data, I show that pedestrian interactions are described by a remarkably simple power law. Unusually, this interaction is based not on the physical separation between pedestrians but on the imminence in time of a potential future collision.

In the second part of the talk I examine a simple model of a traffic network and study how inefficiency in the traffic flow arises from "selfish" decision-making. I show that, for networks comprised of fast roads and slower roads, the network flow becomes maximally inefficient precisely when the proportion of fast roads matches the network percolation threshold. This conclusion suggests a surprising connection between Nash equilibria from game theory and percolative phase transitions from statistical physics.

In December 2012 and January 2013, water levels on Lake Michigan-Huron (the single largest area of fresh surface water on Earth) dropped to record lows (based on a record dating to the mid-1800s). This hydrological event occurred during a period (that begin in the late 1990s) in which the North American Great Lakes have been characterized by above average water temperatures, high evaporation rates, and persistent low water levels. Recent research suggests, however, that the extreme cold winter of 2013-2014 may have significantly lowered the heat content of the Great Lakes, and could signify a transition between hydrological and thermal regimes.

Here, I explore historical drivers of water level change across the Great Lakes, with a particular emphasis on analyzing model simulations and forecasts that propagate changes in regional precipitation, temperature, and evaporation into seasonal and interannual water budget and level dynamics. I assess the skill of these models, and underscore periods when they have performed well, and when they have failed to adequately explain observed water level variability. I conclude with a discussion of water level projections, and the scientific research needed to improve their skill over different time scales.

The droplet formation and production from liquid jets and columns are very familiar and important in every day’s life. The pinching dynamics of liquid thread follows well established laws depending on inertia, viscous effects and capillary forces. However, before breakup, pinched necks reach nanometric dimensions comparable to the scale of ambient thermal fluctuations; this new length scale may play a role in the ultimate pinch-off stage. If in “classical” situations, this thermal regime has no influence on the drop production, the device miniaturization and the increasing use of fluids in nanotechnologies should alert us with example such as flows in nanotubes or thermal annealing of nanowires where the length scale may compare to the thermal length. New rupture mechanisms and then different droplet distributions are expected. Their investigation remains nonetheless a real challenge. A route for investigating this fluctuation-dominated regime consists in using near-critical phase-separated fluids as the amplitude of fluctuations can be tuned with the proximity to the critical point. After an introduction to the dynamic of breakup in the viscous and thermal fluctuation regime, we will illustrate the universal character of these two regimes in near-critical phases of micro-emulsions and demonstrate the existence of a well-defined crossover between them when the neck radius reaches the thermal length. Moreover, we show that the neck morphology becomes symmetric in the thermal fluctuation regime, thus leading to the disappearance of satellite drops and to the production of monodisperse droplets. Finally, we present some further preliminary results on the dynamics of liquid ligaments and nanojet analogs when fluctuations are important.

Conservation of Information (CoI) asserts that the amount of information a search outputs can equal but never exceed the amount of information it inputs. Mathematically, CoI sets limits on the information cost incurred when the probability of success of a targeted search gets raised from p to q (p < q), that cost being calculated in terms of the probability p/q. CoI builds on the No Free Lunch (NFL) theorems, which showed that average performance of any search is no better than blind search. CoI shows that when, for a given problem, a search outperforms blind search, it does so by incorporating an amount of information determined by the increase in probability with which the search outperforms blind search. CoI applies to evolutionary search, showing that natural selection cannot create the information that enables evolution to be successful, but at best redistributes already existing information. CoI has implications for teleology in nature, consistent with natural teleological laws mooted in Thomas Nagel's Mind & Cosmos.

Democratic government is famously plagued by problems such as the tyranny of the majority and political paralysis. These result from fundamental flaws of one-man-one-vote as a mechanism for collective decisions identified by economists. A simple alternative procedure, Quadratic Voting (QV), solves these problems and offers a practical, efficient, simple and robust alternative. Individuals purchase votes using either money or an artificial currency that may be spread across multiple issues and pay the square of the number of votes purchased. QV is efficient because individuals optimally equate the marginal cost of a vote to the benefit they derive from an additional vote and thus set the number of votes purchased proportional to their values for the outcome if all individuals take the chance of their being pivotal in the outcome as approximately constant. This "should" be true in large populations and a number of detailed approximate calculations, intermediate analytic results and numerical simulations have persuaded us of this. However, we have as of yet been unable to rigorously prove the convergence results that we conjecture in detail due to the small probability of a single individual purchasing a large number of votes that turns out to be necessary to sustain equilibrium. After a brief introduction to the motivation, I plan to devote most of the talk to these formal difficulties in hopes of soliciting suggestions on how to clear these roadblocks.

Is it possible to control the shear modulus of a material mechanically? We reconstitute an assembly of cross-linked actin filaments, a major component of cell cytoskeleton, to show that the system has remarkable property to respond under shear in a deformation history dependent manner. When a large shear stress pulse is applied to the system, the system remembers the direction of deformation long after the stress pulse is removed. For next loading cycle, shear response of the system becomes anisotropic; if the applied pulse direction is same as the previous one, the system behaves like a viscoelastic solid but a transient liquefaction is observed if the pulse direction is reversed with respect to the previous one. Further experiments suggest that this anisotropic response comes from stretching dominated and bending dominated deformation directions induced by the large shear deformation giving rise to a direction dependent mechano-memory. The long time scale over which the memory effect persists has relevance in various deformations in cellular and multicellular systems.

The collective actions of heterogeneous individuals determine the course of some of the most intriguing phenomena in nature such as synchronization, flocking, multicellularity and inter-species ecology. In this talk, I will present collective dynamics in two different experimental systems: (i) a surprising symmetry broken synchronization state in coupled mechanical oscillators and (ii) hydrodynamically mediated flocking in a population of self propelled microdroplets.

In the first part, I will talk about an intriguing dynamic referred to as a chimera state. In the world of coupled oscillators, a chimera state is the co-existence of synchrony and asynchrony in a population of identical oscillators, which are coupled nonlocally. Following nearly 10 years of theoretical research, it has been an imminent question whether these chimera states exist in real systems. Recently, we built an experiment with springs, swings and metronomes and realised these symmetry breaking states in a purely physical system. Our mathematical model shows that the self-organization observed in the experiments is controlled by elementary dynamical equations from mechanics that are ubiquitous in many natural and technological systems such as power grids, optomechanical crystals, or cells communicating via quorum sensing in microbial populations.

In the second part, I will talk about microswimmers made from liquid crystalline emulsion droplets. Following a brief description of the swimming mechanism, I will discuss the effects of confinement on the collective effects that emerge in ensembles of millions of swimming droplets. Specifically, I dwell on hydrodynamic and volume exclusion interactions only through which these droplets can couple their motions.

Sleep may well be universal in the animal kingdom. Yet, fundamental aspects of sleep remain controversial and elusive. Questions under debate include universality, natural history, core function, and even the very definition of sleep. Sleep is widely believed to be essential for neural circuit wiring and maintenance, i.e., synaptic plasticity. That said, synaptic changes also take place independently of the sleep/wakefulness state. Moreover, sleep has been hypothesized to either strengthen or downscale synapses. Experimental evidence supporting both possibilities exists, depending on the model animal, brain region, and type of measurement in question. A key feature distinguishing sleep from other states of decreased activity such as paralysis, comatose, anesthesia, hibernation, or torpor, is its intricate homeostatic regulation. Generally, biological homeostasis invokes modulatory responses aimed at stabilizing internal conditions. In the context of sleep, the most obvious manifestation of homeostatic regulation resembles a spring: the more the period of wakefulness is stretched, the stronger the restoring force or tiredness. More detailed measurements reveal various signatures of homeostatic regulation both in sleep-deprived animals and as the normal period of sleep unfolds. This talk will describe experiments performed on a model system that is the simplest to possess a nervous system and the most phylogenetically ancient – the nematode C. elegans. Specifically, it will focus on lethargus, the sleep-like state of C. elegans. Using tunable photo- and mechano-stimulation, we identified two distinct categories of homeostatic responses during lethargus. Within this state, C. elegans exhibits alternating epochs of motion and complete quiescence. The durations of these epochs typically range between 2 and 100 sec. In the presence of weak or no stimuli, extended epochs of motion were found to cause an extension of the subsequent periods of uninterrupted quiescence. In the presence of strong stimuli, the correlations between motion and quiescence were temporarily disrupted and homeostasis manifested as a global elevation of the time spent in quiescence outside the stimulus. Two mutually exclusive mechanisms – neuropeptidergic and transcriptional regulation – were found to play roles in establishing these distinct responses to weak and strong stimuli respectively. Thus, routine stabilization of lethagus is both behaviorally and mechanistically distinct from the compensation for a strong, stressful disruption. These findings add to the list of similarities between C. elegans lethargus and sleep and highlight the importance of neuropeptides in stabilizing this state.

Bridging or connecting the descriptions and models of systems across widely separated scales is a deep problem that permeates many areas of scientific investigation. Unfortunately, philosophical discussion of this problem is often contextualized as an ``all or nothing'' dichotomy between reductionism and emergentism. This is much too crude.

This talk will discuss a set of mathematical techniques including the renormalization group and homogenization theory designed to upscale from models of systems that exhibit heterogeneities at small/micro scales to models that are homogeneous at continuum/everyday scales. The focus will be on two aspects of the use of such techniques. On the one hand, they appear to be essential to explain the existence of certain kinds of patterns in nature and the relative autonomy of the continuum scale models from the lower scale details. Why, for example, do the equations that govern the scaling behavior of different fluids at criticality work so well when they completely ignore molecular scale details? Why, do the Navier-Cauchy equations for bending elastic beams work so well when they, too, essentially fail to reference any atomic or lower scale details?

On the other hand, we can also sometimes use models (toy models or minimal models) to investigate and understand the behavior of real systems. For example, we can employ the Ising model and lattice gas automata to study the behavior of real systems---actual fluids that look absolutely nothing like these models at lower scales. The mathematics of the renormalization group and other techniques provide an account of how such non-representative minimal models can be explanatory and can provide understanding. In this talk I will discuss the importance of these mathematical techniques for answering the questions of autonomy, and the role and effectiveness of minimal models.

To fly is not to fall: not to fall under gravity, and not to fall against instability. To balance in air, insects have to make subtle adjustment to their wing movement so not to tumble. What do insects measure to stabilize their flight? How often and how fast must insects adjust their wings to remain stable? Based on computational analyses of 3D flight dynamics, we recently conjectured that fruit flies sense their orientation every wing beat, or every 4ms, for stable flight. I will discuss the reasonings that led to our conjecture and also describe the method for our computations.

Many airplanes can, or nearly can, glide stably without control. So it seems natural that the first successful powered flight followed from mastery of gliding. Many bicycles can, or nearly can, balance themselves when in motion. Bicycle design seems to have evolved to gain this feature. Also, we can make toys and 'robots' that, like a stable glider or coasting bicycle, stably walk without motors or control in a remarkably human-like way. So it makes sense to use `passive-dynamics' as a core for developing the control of walking robots and to gain understanding of the control of walking people. That's what I used to think. But, so far, this has not led to robust walking robots. What about human evolution? We didn't evolve dynamic bodies and then learn to control them. Rather, people had elaborate control systems way back when we were fish and even worms. But if control is paramount, why is it that uncontrolled passive-dynamic walkers can walk so much like humans? It seems that energy optimal control, perhaps a proxy for evolutionary development, arrives at solutions that have features in common with passive-dynamics. Rather than thinking of good powered walking as passive walking with a small amount of control added, I now think of powered walking as highly controlled, but with much of the motor action titrated out.

This talk is about two classes of (interesting, at least to me) physical behavior that follow from them impossibility of integrating some formulas that involve derivatives. First, systems with wheels or ice skates can be conservative yet have asymptotic stability. This is relevant to braking cars, flying arrows and the balance of skateboards and bicycles. Second, is the well known possibility that a system with zero angular momentum can, by appropriate deformations, rotate without any external torque. This effect explains how a cat that is dropped while upside down can turn over and of how various gymnastic maneuvers are performed. Both rolling contact and constancy of angular momentum are examples of the "non-integrability" of a "non-holonomic" equation. There are various simple demonstrations of these phenomena that can go bad. Cars can crash, bikes fall over and, in terrestrial experiments, various effects can swamp that which one wants to demonstrate. The talk describes the basic theory and then a collection of simple experiments that fail various ways for various reasons.

Oil-based enamel paints, manufactured for household and other uses in the beginning of the twentieth century became popular among avant-garde European painters because of their surface qualities and handling properties: Pablo Picasso, Wassily Kandinsky, Francis Picabia, René Magritte and others are reported to have used Ripolin house paints in their works. These paints were so renowned that the term ‘ripolin’ was often used to refer to a broader class of enamel paints in general and soon became synonymous with modernity, sophisticated technology, excellent quality and high performance. Surprisingly, little attention has been given to the study of industrial paint chemistry and technology including house, architectural, car and boat paints produced in the beginning of the twentieth century. For the past several years a research project has been carried out at the Art Institute of Chicago to fill this gap, approaching the study through sophisticated scientific analysis, in-depth study of the industrial technical literature of the time, and analysis of paintings by Pablo Picasso and his contemporaries.

The analysis of artists’ paints, hierarchically complex materials typically composed of binder, pigments, fillers, and other additives is a challenging, multiscale problem. Techniques as simple as visual observation under a visible light stereomicroscope and as complex as high resolution nanoprobe Synchrotron Radiation-X-ray fluorescence (SR-XRF) mapping are deployed by museum scientists to answer questions about composition, stability, manufacturing technology, and even the artist’s intention.

For the past eleven years a state of the art scientific laboratory has been developed at the Art Institute of Chicago to enhance our understanding and long-term preservation of the works in the collection. In this talk Dr. Casadio will present a behind the scenes look at the research taking place in preparation for exhibitions and scholarly catalogues. Part forensic science, part detective work, this lecture will unravel the creative and technical feats of art giants such as Pablo Picasso. It will illuminate how the tools of science and archival research into technical and industrial sources can shed new light on the work of conservators and art historians and potentially alter the way in which the public looks at each work of art.

This will be one person's take on the spectrum of career paths outside of physics. I will discuss my own experience,and where the next opportunities seem to be headed. Much of my experience has been in the financial sector so I will focus on it. Finance happens to be in the midst of massive changes and the opportunities of the past are not likely to be the opportunities of the future. I've also had the opportunity to see various transitions from academia to business and will offer examples of what has worked and not worked (including my mistakes!).

A microscopic understanding of their mechanical response, and flow under applied stress, of amorphous solids is of considerable current interest. Computational investigations of the response of model amorphous solids reveals rich phenomenology and provide insights into the nature of the yielding of such solids. A dynamical transition, related to yielding, is observed when the amplitude of oscillatory shear deformation is varied: For large values of the amplitude the system exhibits diffusive behavior and loss of memory of the initial conditions, whereas localization -- but with interesting periodic orbits -- is observed for small amplitudes. In the localization regime, interesting memory effects are observed, involving the possibility of storing persistent multiple memories. In hard and soft sphere packings modeling granular matter, instead, shear deformation leads to structures with interesting geometric signatures that are revealed by the analysis of the void space in such structures, and are argued to underlie shear jamming under suitable conditions.

The concept of radiative-convective equilibrium (RCE) is the simplest and arguably the most elegant model of a climate system, regarding it as a statistically one-dimensional balance between radiative and convective heat transfer. In spite of this, RCE is seldom studied and poorly understood today. Recent advances in cloud-system-resolving numerical models have made it possible to explicitly simulate such states, simulating the convective plumes themselves rather than representing them parametrically. The simulations reveal a startling phenomenon: Above a critical surface temperature, moist convection spontaneously aggregates into a single cluster, in a non-rotating system, or into multiple tropical cyclones on a rotating planet. I will show that this results from a linear instability of the RCE state, and this this instability migrates the RCE state toward one of the two stable equilibria. This instability represents a subcritical bifurcation of the ordinary RCE state, leading to either a dry state with large-scale descent, or to a moist state with mean ascent; these states may be accessed by finite amplitude perturbations to ordinary RCE in the subcritical state, or spontaneously in the supercritical state.

Satellite pictures indicate that plankton-life in the oceans exhibit 'foliated' structures on many length scales clearly influenced by the turbulent flows in the water. We formulate a particle model where plankton are advected in a model field of strong turbulence. The model indicates a huge drop in the carrying capacity due high concentrations in the stagnation points of the flow. For two neutral alleles, we find that the presence of turbulence diminishes the fixation time significantly. We further study the fixation time as a function of various flow parameters and obtain analytical expressions for the fixation probability without flows. Simulations of the model in zero and one dimensions give good agreement with theoretical predictions both when species experience competitive exclusions and when they co-exist under mutualistic behavior. We also briefly discuss some general properties of turbulence and shell models.

Black holes are an exquisite testing ground for our understanding of quantum gravity. Particularly vexing puzzles have arisen in trying to understand how and why black holes behave as thermodynamic objects, having a temperature proportional to Planck's constant, and therefore by the first law an entropy inversely proportional to it. Hawking's calculation of the black hole blackbody spectrum raises further issues about how locality and causality can be consistent with quantum mechanical unitarity. After briefly reviewing these properties, I will present an overview of how string theory is answering these challenges using exotic phases of matter only available in a theory of extended objects inhabiting extra dimensions of space, and the additional topological complexity such geometries afford.

Recent advances in nanotechnology have enabled researchers to control individual quantum mechanical objects with unprecedented accuracy, opening the door for both quantum and extreme-scale conventional computing applications. As these devices become larger and more complex, the ability to design them for simple control becomes a daunting and computationally infeasible task. Here, motivated by ideas from compressed sensing [1,2], we introduce a protocol for Compressed Optimization of Device Architectures (CODA) [3]. It leads naturally to a metric for benchmarking device performance and optimizing device designs, and provides a scheme for automating the control of gate operations and reducing their complexity. Because CODA is both experimentally and computationally efficient, it is readily extensible to large systems. We demonstrate the CODA benchmarking and optimization protocols through simulations of up to eight quantum dots in devices that are currently being developed experimentally for quantum computation.

[1] E. J. Candès, J. K. Romberg, and T. Tao, Communications on Pure and Applied Mathematics, 59, 1207 (2006) [2] D. Donoho, IEEE Transactions on Information Theory, 52, 1289 (2006) [3] A. Frees et al., arXiv:1409.3846

Collective migration of eukaryotic cells plays a fundamental role in tissue growth, wound healing and immune response. The motion, arising spontaneously or in response to chemical and mechanical stimuli, is also important for understanding life-threatening pathologies, such as cancer and metastasis formation. We present a phase-field model to describe the movement of many self-organized, interacting cells. The model takes into account the main mechanisms of cell motility - actomyosin dynamics, as well as substrate-mediated and cell-cell adhesion. It predicts that collective cell migration emerges spontaneously as a result of inelastic collisions between neighboring cells: collisions lead to a mutual alignment of the cell velocities and to the formation of coherently-moving multi-cellular clusters. Small cell-to-cell adhesion, in turn, reduces the propensity for large-scale collective migration, while higher adhesion leads to the formation of moving bands. Our study provides valuable insight into biological processes associated with collective cell motility.