Eric Sembrat's Test Bonanza

Superconducting Josephson Junctions are one of the most active areas of research in Condensed Matter Physics today.  One unique aspect of Josephson Junctions is the nonlinear relation between the phase of the wave function and the supercurrent flowing though the junction.  This manifests itself in a nonlinear, pendulum-like equation for the dynamics of the phase when the junction is placed in circuit.  Josephson junctions can be fabricated with adjustable parameters, measured in a straightforward fashion, and easily scaled to large network sizes.  In addition, a large Josephson junction circuit measured over a long time contains dynamics which would essentially be impossible to calculate on a computer, but which can be observed with electrical measurements.  This talk will discuss some collective, emergent behavior of Josephson junction networks.  First, we will discuss our work on soliton-like modes called fluxons, which have particle-like properties in a parallel array (1,2).  Next, we will discuss the Kuramoto-like synchronization of a system of disordered oscillators.  Finally, we will show how a circuit of Josephson junctions can be designed to accurately model the time-dependent voltage of a biological neuron (3).  This has a longer-term goal of studying the emergent behavior of a large, coupled neural network.

(1)    “Experimental observation of Fluxon Diffusion in Josephson Rings,” K. Segall, A. Dioguardi, N. Fernandes and J.J. Mazo, Journal of Low Temperature Physics 154, 41-54 (2009).
(2)    “Thermal depinning of Josephson Fluxons in superconducting rings,” J.J. Mazo, F. Naranjo and K. Segall, Physical Review B78, 174510 (2008).
(3)    “Josephson junction simulation of neurons,” P. Crotty,  D. Schult and K. Segall, Physical Review E 82, 011914 (2010).

The Nobel prize in Chemistry 2011 was awarded to Dan Shechtman for his “Discovery of Quasicrystals”. This discovery published in a seminal paper in November 1984 [1] lead to the re-definition of crystalline structures. What Shechtman has observed is a long-range icosahedral symmetry in an aluminum –based alloy. Five-fold symmetry is in clear violation of periodic order, which was the paramount dogma of crystallography. To reconcile a discrete diffraction diagram and forbidden symmetry has required, not without resistance from the community, to reconsider what was known for centuries about crystalline order and to realize that what Shechtman had observed was a new type of atomic structure, which is non periodic yet perfectly ordered.

Quasicrystals of various symmetries have been now observed in a number of compounds, man-made and natural. Quasicrystals is a new cross-disciplinary field of study, reaching to chemistry, physics and mathematics. I will mainly discuss the structure of quasicrystals, the aesthetics of their order based on the golden mean. I will touch upon fundamental questions like what becomes of properties, for instance electronic transport, for quasiperiodic rather than the usual periodic ordered structures.

 [1] Dan Shechtman, I. Blech, D. Gratias, J. Cahn, Phys. Rev. Lett. 53, 1951 (1984).

Albert Fert, Nobel Prize in Physics 2007

Joint colloquium between the School of Physics and MRSEC

Spintronics exploits the influence of the electron spin orientation on electronic transport. It is mainly known for the “giant magnetoresistance” (GMR) and the large increase of the hard disc capacity obtained with read heads based on the GMR, but it has also revealed many other interesting effects. Today spintronics is developing along many novel directions with promising prospects as well for short term applications as for the “beyond CMOS” perspective. After an introduction on the fundamentals of spintronics, I will review some of the most interesting emerging directions of today: spin transfer and its applications to STT-RAMs or to microwave generation, spintronics with semiconductors, graphene and carbon nanotubes, Spin Hall Effects, neuromorphic devices etc.

The dynamics of viscous or viscoelastic membranes surrounded by a viscous fluid plays an important biophysical role in, e.g., understanding the mobility of proteins in cell membranes. These fluid membranes also provide an interesting physical system in which low Reynolds number hydrodynamics acquires an inherent lengthscale, and where membrane curvature can dramatically change the mobility of membrane-bound particles. In this talk I first discuss the hydrodynamics of flat fluid membranes surrounded by bulk fluids, initially developed by Saffman and Delbrück (SD). I then extend these theories to study flows in curved membranes, showing how curvature modifies the SD picture. Finally, I use these geometric ideas to study the effect of curvature on the fluctuation spectrum of (visco-)elastic membranes, and apply that analysis to membrane microrheology. Using this theory, I analyze the fluctuation spectrum of human red blood cell membranes (measured by G. Popescu, UIUC) in order to extract their mechanical properties in various morphological states of the cell.

In 1998 two rival teams of astronomers studying exploding white dwarf stars, called type Ia supernovae, came to the surprising conclusion that the expansion of the Universe is speeding up. This discovery of "the accelerating Universe" ushered in a revolution in our cosmological understanding. I will describe the steps leading to this discovery, and how observations of supernovae from telescopes on the ground and in space can be used to trace the history of cosmic expansion. The continued study of these stellar explosions will shed light on the mysterious "dark energy" that dominates and drives our accelerating Universe.

Ion channels play vital cellular functions.  How an external simulation (e.g., cross-membrane voltage, binding of a ligand, or decrease in external pH) triggers the opening of an ion channel is at the core of its functional mechanism.  We have used molecular dynamics simulations and other computational techniques to develop models for the functional mechanisms of several ion channels, including a nicotinic acetylcholine receptor, an AMPA-subtype glutamate receptor, and the M2 proton channel of the influenza virus.  A very useful way to validate these mechanistic models is to compare changes in residue solvent accessible areas against substituted cysteine accessibility measurements.  For the M2 proton channel, we have developed a theory for calculating the rate of ion transport, based on the proposed functional mechanism.  The permeant proton is modeled as binding obligatorily to a histidine tetrad within the channel pore and then being released to the other side of the membrane, and the rate constants are calculated by modeling these steps as diffusion-influenced reactions.  This calculation of the ion transport rate bridges two traditional approaches that have been pitted against each other, one based on modeling ion permeation as continuous diffusion and the other based on modeling the transport by discrete-state rate equations.  We show that the two approaches give the same ion transport rate and thus settle a long-standing debate.

The Kepler Mission, NASA Discovery mission #10, is specifically designed to survey a portion of our region of the Milky Way galaxy to discover dozens of Earth-size planets in or near the habitable zone and determine how many of the billions of stars in our galaxy have such planets. Results from this mission will allow us to place our solar system within the continuum of planetary systems in the Galaxy.

The Vlasov-Poisson and Vlasov-Maxwell equations possess various variational formulations or action principles. I will discuss a particular variational principle that is based on a Hamiltonian-Jacobi formulation of Vlasov theory, a formulation that is not widely known. I will show how this formulation can be reduced for describing the Vlasov-Poisson system. The resulting system is of Hamilton-Jacobi form, but with nonlinear global coupling to the Poisson equation. A description of phase (function)space geometry and relation to Hamilton-Jacobi PDE methods and weak KAM will be given.

H. Ye and P. J. Morrison Phys. Fluids 4B, 771 (1992). D. Pfirsch, Z. Naturforsch. 39a, 1 (1984); D. Pfirsch and P. J. Morrison, Phys. Rev. 32A, 1714 (1985).

Topological insulators, a novel kind of three-dimensional insulators can have a bulk insulating gap but non-trivial topological surface states. The surface states of these topological insulators show Dirac-like behavior with the spin polarization locked perpendicular to the electron momentum by the effect of strong spin-orbit interaction. As the locking protects the surface electrons from back scattering, they are predicted to have high mobilities. The surface state of Bi₂Se₃ and Bi₂Te₃ topological insulators has been observed by angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM), but is still considered a challenging problem for electronic transport measurements due to the dominant bulk conductance in the materials. We have found that by chemical doping, the chemical potential can be tuned to fall inside the band gap and therefore suppress the bulk conductivity. The Bi₂Se₃ topological insulator can also be tuned to a bulk superconductor, with T_c ~ 3.8 K, by copper intercalation in the van der Waals gaps between the Bi₂Se₃ layers. This shows that Cooper pairing is possible in Bi₂Se₃ with implications for study of Majorana fermion physics and potential quantum computing devices. Furthermore, Mn-doped Bi₂Te₃ has ferromagnetic transition at about 13 K, suggesting that it may be a magnetic topological insulator.

Advances in microscopy have enabled measurements in living cells, but there is a wealth of biologically relevant dynamical information contained in experimental data that has not been utilized.  Existing analysis methods either coarse grain too much or cannot overcome some technical challenges inherent to in vivo measurements. The importance of more fully utilizing information “hidden” in noisy 3D in vivo measurements will be emphasized in several problems.  In this talk, I demonstrate how recent advances in time series analysis can be used to estimate stochastic differential equations (SDEs) and construct hypothesis tests checking the consistency of a fitted model with a single experimental trajectory. The inferred SDE parameters change in a statistically significant fashion over the lifetime of a single trajectory, so methods capable of rigorous statistical inference checking all SDE model (and measurement noise) assumptions using only one time series are valuable.   Analyzing a single trajectory is important for quantitatively identifying heterogeneity in noisy complex systems.  The methods discussed offer new tools for quantitatively probing molecular traffic in the cytoplasm and also enable new discoveries. Although the results presented are centered around the analysis of experimental  mRNA in live yeast cells (Saccharomyces Cerevisiae), the work is also relevant to tracking groups of particles in crowded, noisy, complex environments.