Seminar

The scientific community has been striving for decades to generate biomimetic materials to access many of the beneficial properties seen in Nature. Significant efforts have been devoted to systems that contain a small number of variables and can be mastered without too many unknowns. However, there has been limited success in generating complex systems as seen in Nature. As the systemic complexity increases, the phase diagram becomes less manageable with many possible states and kinetic pathways. Our central hypothesis is that rational design can lead to control over system energy...

Which physical properties of 2D and layered materials can we exploit for powering the next generation of devices that power all of classical information systems?  And which 2D materials are showing promise to enable the future quantum information systems, and why? I will discuss the two questions above. The first question will lead us to the quantum mechanical roots of why current state of the art transistors are slipping away ~1000x more energy than what is needed for logic operations.  And more so than logic, the bottleneck of memory devices threatens to significantly throttle increased...

Abstract: A new direction in topological quantum matter research is the exploration of the large class of nonsymmorphic metals which include glide symmetry operations in their space group (a glide gx =Mx.T is a mirror reflection Mx combined with a fractional translation T in the mirror plane). The layered material KHgSb is analogous to stacking graphene together with distinct ions in the A and B sublattices. A half-lattice translation between adjacent layers renders it nonsymmorphic. KHgSb has been predicted to feature double quantum spin Hall (QSH) surface states in addition to hourglass...

Light-matter interaction is at the heart of most optical processes we are familiar with such as absorption, emission and scattering. These are normally treated by assuming that the incident light does not significantly modify the underlying electronic states of the material it interacts with. The strong coupling regime consists of the extreme case where light-matter interaction is so strong that it must be treated non-pertubatively. Polaritons, the resulting mixed light-matter particles, can be the source of many unique phenomena. We will describe how these quasiparticles can be exploited...

How do fluids become turbulent as their flow velocity is increased? In recent years, careful experiments in pipes and Taylor-Couette systems have revealed that the lifetime of transient turbulent regions in a fluid appears to diverge with flow velocity just before the onset of turbulence, faster than any power law or exponential function. I show how this superexponential scaling of the turbulent lifetime in pipe flow is related to extreme value statistics, which I show is a manifestation of a mapping between transitional turbulence and the statistical mechanics model of directed percolation.  This mapping itself arises from a further surprising and remarkable connection: laminar and turbulent regions in a fluid behave as a predator-prey ecosystem. Such ecosystems are governed by individual fluctuations in the population and being naturally quantized, are solvable by path integral techniques from field theory. I explain the evidence for this mapping, and propose how a unified picture of the transition to turbulence emerges in systems ranging from turbulent convection to magnetohydrodynamics. 

Empirical evidence suggests that living neural networks operate near a continuous phase transition, conjectured to be an optimal point for information storage and processing. Applying theoretical approaches, however, is challenging since vital features of neural networks present numerous obstacles to the applicability of traditional statistical physics tools, many of which have not yet been adapted to neuroscience. I will describe a simple cellular automaton model which allows for the characterization of the out-of-equilibrium transition and demonstrates an explicit symmetry breaking due...