This talk shows that without quantum correlations, energy cannot flow. The result follows from a simple theorem that shows that systems whose dynamics do not generate quantum discord are effectively non-interacting. I show that the rate of heat transfer between two quantum systems at different temperatures is directly proportional to the instantaneous rate of increase in discord. I report the results of a measurement that measures the increase in discord due to nanoscale heat flow across an aluminum-sapphire interface and to be 4.28 * 10^{24} bits per sec per square meter per degree K.

Machine-learning tasks frequently involve problems of manipulating and classifying large numbers of vectors in high-dimensional spaces. Quantum computers are good at manipulating high-dimensional vectors in large tensor product spaces. This talk shows how quantum computers can provide an exponential speed-up over their classical counterparts for a variety of problems in machine learning and big data analysis.

Biological transport webs, such as the blood circulatory system in the brain and other animal organs, or the slime mold Physarum polycephalum, are frequently dominated by dense sets of nested cycles. The architecture of these networks, as defined by the topology and edge weights, determines how efficiently the networks perform their function. In this talk we present some general models regarding the emergence and extraction of hierarchical nestedness in biological transport networks. In particular, we discuss how a hierarchically organized vascular system is optimal under conditions of variable, time-dependent flow, but also how it emerges naturally from a set of simple local feedback rules. To characterize the topology of these weighted cycle-rich network architectures, we develop an algorithmic framework that analyzes how the cycles are nested. Finally, using this algorithmic framework and an extensive dataset of more than 180 leaves and leaflets, we show how the hierarchical organization of the nested architecture is in fact a distinct phenotypic trait, akin to a fingerprint, that characterizes the vascular systems of plants and can be used to assist species identification from leaf fragments.

I will discuss strange and unexpected connections between conformal field theory, the representation theory of sporadic finite simple groups, and both modular and mock modular forms.

The Biermann Battery effect is frequently invoked in cosmic magnetogenesis and in High-Energy Density laboratory physics experiments. Unfortunately, it has recently been noticed that direct implementations of the Biermann effect in MHD codes produce unphysical magnetic fields at shocks, whose value does not converge with resolution. This convergence breakdown, which has affected all Eulerian and Lagrangian MHD codes implementing the Biermann effect, is due to naive discretization, which fails to account for the fact that discretized irrotational vector fields have spurious solenoidal components that grow without bound near a discontinuity. I show that careful consideration of the kinetics of ion viscous shocks leads to a formulation of the Biermann effect that gives rise to a convergent algorithm. I also note a novel physical effect: a resistive magnetic precursor in which Biermann-generated field in the shock "leaks" resistively upstream. The effect appears to be potentially observable in experiments at laser facilities.

A fundamental goal of neuroscience is to understand how the activity of neurons in networks gives rise to coordinated behaviors. Our laboratory studies brain and behavior in the roundworm Caenorhabditis elegans. Advantages of this 1-mm long creature include a compact and extraordinarily well-mapped nervous system, genetic manipulability, and optical transparency, and an ever-expanding set of tools for measuring and manipulating activity in its nervous system. In particular, we have developed methods for optogenetically manipulating specific neuron types in freely behaving animals. We describe our efforts to understand the neural circuits underlying two fundamental, rhythmic behaviors: feeding and locomotion.

Frames consisting of nodes connected pairwise by rigid rods or central-force springs, possibly with preferred relative angles controlled by bending forces, are useful models for systems as diverse as architectural structures, crystalline and amorphous solids, sphere packings and granular matter, networks of semi-flexible polymers, proteins, origami, and an increasing number of lab-constructed micron-scale metamaterials. The rigidity of these networks depends on the average coordination number z of the nodes: If z is small enough, the frames have internal zero-frequency modes, and they are “floppy”; if z is large enough, they have no internal zero modes and they are rigid. The critical point separating these two regimes occurs at a rigidity threshold that for central forces in d-dimensions occurs at or near coordination number zc = 2d. At and near the rigidity threshold, elastic frames exhibit unique and interesting properties, including extreme sensitivity to boundary conditions, power-law scaling of elastic moduli with (z- zc), and diverging length and time scales.

This talk will explore elastic and mechanical properties and mode structures of model periodic lattices, such as the square, kagome, pyrochlore, and jammed packings with central-force springs, that are just on verge of mechanical instability. It will discuss the origin and nature of zero modes and elasticity of these structures under both periodic (PBC) and free boundary conditions (FBC), and it will investigate lattices (a) whose zero modes under the two boundary conditions are essentially identical, (b) whose phonon modes in the bulk are “gapped” with no zero modes in the periodic spectrum (except at zero wavenumber) but include zero-frequency surface Rayleigh waves in the free spectrum, and (c) whose bulk phonon modes include isolated points or lines where their frequency is zero. In case (a), lattices are generally in a type of critical state that admits states of self-stress in which there can be tension in bars with zero force on any node. Distortions away from that state gap the spectrum and give rise to surface modes under free boundary conditions whose degree of penetration into the bulk diverges at the critical state. The gapped states have a topological characterization, similar to those of polyacetylene and topological insulators, that define the nature of zero-modes at the boundary between systems with different topology. Case (c) is closely analogous to Weyl semi-metals with isolated points in the Brillouin zone where valence and conduction bands meet. These critical lattices generally have macroscopic elastic distortions, called Guest Modes, that cost no energy.

A wide range of observations support the conclusion that most of the matter in our universe is not made of protons, neutrons, or electrons, but of some other substance or substances that do not interact electromagnetically or through the strong nuclear force. For a lack of a better name, we simply call this stuff "dark matter". I'll discuss some of our best hypotheses for what dark matter might be made of, and the experimental program designed to test this list of possibilities. I'll focus in particular on searches for dark matter annihilation products using gamma-ray telescope, which may have already seen the first evidence of particle dark matter interactions.

Population structure is a fundamental feature of genetic data that has importance for addressing questions in evolutionary biology, conservation genetics, and trait mapping. In humans, population structure can give perspective on human origins and history, shed light on evolutionary processes that have shaped human adaptation and disease, and must be understood for effectively carrying out global medical genetics and personalized medicine. Techniques for elucidating population structure rely heavily on a suite of statistical methods with various tradeoffs. In this talk, I will review several important models and methods for studying population structure, with a special focus on methods for studying spatially distributed data. The methods covered will include principal components analysis, admixture methods, and a method that explicitly models spatial inhomogeneity in patterns of structure. The applications will be drawn mainly from analysis of human genetic data.

Molluscan animals such as squids, octopuses and clams build an array of living optical devices of astounding optical/photonic sophistication and complexity, such as structural camouflaging coatings, graded index lenses, solar radiance distributors, and wavelength-specific light guides. Unlike the iridescent structures in fish, butterflies and birds, the "iridocytes" in molluscs are formed from still-living cells, with the high-index portions generated by dense assemblies of protein in the active cytoplasm. These optically resonant cells seem to be allowed more structural diversity than the systems evolved in other taxa, and have resulted in solutions to a wider array of evolutionary optical problems than in any other animal group, including underwater vision, emissive camouflage, reflective camouflage, and distribution of light for efficient photosynthesis. Several new observations about reflectin and S-crystallin proteins from squids show that the soft matter physics construct of "patchy colloids” is probably the most informative paradigm for understanding the assembly of these living photonic systems. This talk will discuss our recent discoveries of optical function and self-assembly in squid vision, squid camouflage, and "solar transformers" in giant clams.

Yield-stress fluids, including gels and pastes, are effectively fluid at high stress and solid at low stress. In liquid-solid impacts, yield-stress fluids can stick and accumulate where they impact, motivating several applications of these rheologically-complex materials (including fire suppression and spray coating). Here we experimentally study yield-stress fluids impacting three types of surfaces where they may (or may not!) stick: pre-coated surfaces, hot surfaces, and permeable surfaces. Using high-speed video and quantitative analysis, we report various regimes of splashing, Leidenfrost effects, and flow-through. Existing dimensionless groups do not adequately characterize all these regimes. Incorporating relevant lengthscales, we demonstrate successful dimensionless groups that organize the dynamics into a lower-dimensional space. This provides insight into the physics of droplet impact problems. Moreover, it potentially allows for fluid design and extrapolation of these results to dynamically and geometrically similar situations beyond the explicit material and parameter values explored here.

The programmable selectivity of DNA recognition constitutes an elegant scheme to self-assemble a rich variety of superlattices from versatile nanoscale building blocks. We describe the design of superlattices by using the high selectivity of DNA recognition “imprinted” in DNA functionalized nanoparticles via a scale-accurate coarse-grained model that captures the dynamic nature of DNA hybridization events. The model reproduces the experimentally-observed crystallization behavior of various mixtures of DNA-modified nanoparticles and the assembly into superlattices single crystals with specific Wulff shapes. Besides spherical DNA functionalized gold nanoparticles, the model describes the assembly of nanoparticles with anisotropic regular shapes including cubic and octahedral shapes, and irregular shapes akin to those exhibited by enzymes into superlattices, and the emergence of broken symmetries such as a BCT lattices in homogeneously functionalized gold nanocubes. We discuss the key ingredients necessary for achieving the assembly of regular and anisotropic DNA functonalized gold nanoparticles and of DNA functionalized proteins into specific superlattices.

Cooperative transport of large items is a behavior that is extremely rare outside humans and ants. Indeed, this is a complex behavior that requires non-trivial coordination not only in tugging but also in more cognitive tasks such as navigation and problem solving. I will present several aspects of this behavior while focusing on the origins of this group cognition. Is it a manifestation of the abilities of a single ant or, rather, an emergent consequence of the communication between a large number of individuals?

Tau, an intrinsically disordered protein expressed in neuronal axons, binds to microtubules and regulates their dynamics. Tau dysfunction is unequivocally linked to neurodegenerative diseases (including Alzheimer’s, chronic traumatic encephalopathy) but the molecular mechanism of Tau-induced microtubule bundling remains unknown. Although there have been observations of string-like microtubule bundles in the axon initial segment and hexagonal bundles in non-neuronal cells overexpressing Tau, cell free reconstitutions have been unable to replicate either geometries. I will report the energy landscape of Tau-mediated, GTP-dependent “active” microtubule bundles through synchrotron SAXS and TEM. For the first time, I show that Tau acts to attract microtubules into bundles of both geometries, as opposed to the previously presumed role of repulsive spacer. The anionic block repulsions of Tau compete with transient, short-range charge-charge attractions in opposing, weakly penetrating Tau distal domains. The sum of these sub-kBT interactions over the entire microtubule length stabilizes microtubules into bundles, reconciling previous non-observations of bundles with shorter microtubules. Through this length-dependent mechanism, Tau is able to both specifically bind to microtubules and act as a dynamic chain in bundling microtubules through non-specific electrostatic interactions instead of the more common static cross-linkages mediated through the specific interactions of folded proteins.

What determines shape? Energy minimization in flexible systems with competition between order and shape change can lead to a wide variety of shapes including highly faceted singular structures. I will discuss shape generation and shape shifting in two systems – molecularly thin vesicles with liquid crystalline order and fluid droplet networks with osmolarity gradients.

It is a common observation that technology can change and augment the way we think. In one common account, we outsource problem-solving to technology: we ask questions of search engines, use maps to navigate and understand our environment, and so on. In this talk I develop the more radical idea that our thoughts themselves are, in important ways, technologies. In particular, by inventing more powerful user interfaces, we can expand the range of thoughts human beings can think. I will discuss numerous examples, including interfaces for exploring 4-dimensional space, Euclidean geometry, and several other domains traditionally regarded as difficult for humans to think about.

Active or energy-consuming microparticles are intrinsically out-of-equilibrium. This renders their physics far richer than passive colloids and give rise to the emergence of complex phenomena e.g. collective behavior or self-propulsion.. I will present a variety of non-equilibrium phenomena observed with experimental realization of synthetic micro swimmers: dissipative self-assembly, sensing of the environment, or effective interactions, in the absence of any potential...

Life expectancy at birth has increased dramatically, but the span over which individuals retain high levels of well-being—their healthspan—has not increased. To provide insight into genetic and environmental factors that affect the advance of physiological age relative to chronological age, we aim to develop a new biological framework, or “ruler,” that can precisely quantify healthspan in nematodes and shed light on healthspan across species. Our goal is to substantially advance the fundamental understanding of myriad interconnected factors that affect physiological aging. We have analyzed massive amounts of behavioral data for aging nematodes with the goal of developing novel quantitative measures of behavior phenotypes.

I will discuss a Monte Carlo approach to computing statistical averages that is based on a decomposition of the target average of interest into subproblems that are each individually easier to solve and can be solved in parallel. It is a close relative of the classical stratified sampling approach that has long been a cornerstone of experimental design in statistics. The most basic version of the scheme computes averages with respect to a given density and is a generalization of the umbrella sampling method for the calculation of free energies. For this scheme we have developed error bounds that reveal that the existing understanding of umbrella sampling is incomplete and potentially misleading. We demonstrate that the improvement from umbrella sampling over direct simulation can be dramatic in certain regimes. Our bounds are motivated by new perturbation bounds for Markov Chains that we recently established and that are substantially more detailed than existing perturbation bounds for Markov chains. I will also briefly outline a ``trajectory stratification’’ technique based on the nonequilibrium umbrella sampling method, that extends the stratified sampling philosophy to the calculation of dynamic averages with respect a given Markov process. The scheme is capable of computing very general averages and offers a natural way to parallelize in both time and space.

We are customarily taught to understand ordinary solids by considering perturbations about a perfect crystal. This approach becomes increasingly untenable as the amount of disorder in the solid increases. In a crystal with only one atom per unit cell, all atoms play the same role in producing the solid's global response to external perturbations. Disordered materials are not similarly constrained and a new principle emerges: independence of bond-level response. This allows one to drive the system to different regimes of behavior by successively removing individual bonds. We can thus exploit disorder to achieve unique, varied, textured and tunable global response. We can use similar pruning techniques to achieve long-range interactions inspired by allosteric behavior in proteins. This allows a local input strain to control the local strain at a distant site in the network.

The dynamics of the canopy in a tropical rain forest can be described as a zero-sum game: a tree falls, and the gap in the canopy ignites competition among the seedlings, with the winner filling the gap. The analogy with zero-sum games allows connecting this problem with well-studied models in game theory and evolutionary game theory. In the simplest model of this type, dominance among seedlings is encoded in a tournament, a graph in which for each pair of species a directed edge connects the loser to the winner. Every time a gap arises, two seedlings compete for filling the gap, and the winner is chosen following the corresponding edge in the tournament. Dynamics lead to two possible outcomes: monodominance, in which only one species remains, or coexistence among an odd number of species, neutrally cycling around an equilibrium point.

Higher-order interactions, in which the presence of a species modifies the relationship between other species, have long been recognized as an important process in ecology. To this date, however, their effect on community dynamics is poorly understood. Here we show that in models for canopy dynamics, allowing for more than two seedlings at a time to compete creates higher-order interactions that automatically stabilize dynamics, leading to a globally stable equilibrium.

The same result holds when we relax the rules of the competitive game, allowing a species to dominate another only in probability. In this generalization, an even number of species can coexist, and for each possible species abundance distribution we can find a model that would produce the target distribution at equilibrium.

The ability to reconfigure elementary building blocks from one structure to another is key to many biological system. Bringing the intrinsic adaptability of biological systems to traditional synthetic materials is currently one of the biggest scientific challenges in material engineering. Here we introduce a new design concept for the experimental realization of self-assembling systems with built-in shape-shifting elements. We demonstrate that dewetting forces between an oil phase and solid colloidal substrates can be exploited to engineer shape-shifting particles whose geometry can be changed on demand by a chemical or optical signal. We find this approach to be quite general and applicable to a broad spectrum of materials, including polymers, semiconductors and magnetic materials. This synthetic methodology can be further adopted as a new experimental platform for designing and rapidly prototyping functional colloids, such as reconfigurable micro swimmers, colloidal surfactants and switchable building blocks for self-assembly.

The simple process of crumpling a sheet of paper with our hands results in a complex network of interconnected permanent creases of many sizes and orientations. Sheet preferentially bends along these creases, introducing history dependence to the process crumpling. I will present an experimental study of the dynamics of crumpling. Specifically, I will first discuss how a crease network evolves when a thin elastoplastic sheet is repeatedly crumpled, opened up and then re-crumpled. Is there a maximally crumpled state after which the flat sheet can be deformed without further plastic damage? If time permits, I will also I'll describe our investigation of the properties of highly crumpled thin sheets, which exhibit unusual mechanical properties. Including slow relaxations, memory effects and intermittent response to a continues drives.

Topological insulators are solid-state materials whose transport properties are immune to defects and disorder due to underlying topological order. Perhaps the first such phenomenon was the quantum Hall effect, wherein the Hall conductivity is quantized and hence extremely robust. In this talk, I will present the experimental observation of the topological protection of the transport of photons (rather than electrons in the solid state) in a complex dielectric structure. Time permitting, I will discuss the observation of the topological Anderson insulator phase for photons as well as the observation of optical Weyl points in three dimensions.

Textbook fluid mechanics focuses on steady flows past rigid objects, but Nature rarely obeys such restrictions and instead offers fascinating problems involving the coupled dynamics of bodies and flows. Drawing inspiration from biological and geophysical flows, our Applied Math Lab approaches fluid-structure interaction problems through tabletop experiments. I’ll present studies into two topics: Schooling and flocking, which involves flow-mediated interactions among many swimmers or flyers; and Geomorphology, or the sculpting of a boundary due to erosion or dissolution by flows. In these problems, memory or history-dependence plays an important and unexpected role. For schooling, we show that collective behavior arises from the storage of information in the flow field by one swimmer that is then recalled later by another. And we show that as erosion works to modify the shape of an object, this process sometimes maintains a memory of initial conditions and in other cases undergoes a memoryless pursuit of a universal shape.

Melting in two dimensions is characterized by the thermal excitation and proliferation of free topological defects, disclinations and dislocations which destroy the rigidity of the crystal. This freezing/melting process has been well established for flat systems especially for dipolar, U(r) ~1/r3 potentials, with control parameter, Γ = U(a)/kBT, where a is an interparticle spacing. The flat spacing freezing occurs at Γ ~ 70. On a sphere topology requires that there must be a net 12 pentagons (1/2 disclinations) i.e. the 12 pentagons on a soccer ball, and energetically it is favorable to screen the pentagons with strings of dislocations (pentagon-heptagon pairs) known as “scars”. Our system consists of charged colloidal particles in an oil droplet in water bound to the inner surface by image charges. We study particle mean square displacement, hexagonal order, defect structure, and scar-scar correlations by confocal microscopy for droplets of different Γ and number of particles. Freezing on sphere proceeds by the formation of a single, encompassing, crystalline “continent” that forces the defects into 12 isolated “seas” with icosahedral symmetry at the flat space value of Γ ~ 70.