Eric Sembrat's Test Bonanza

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).

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).

In the framework of the Fitzhugh-Nagumo kinetics and the oscillatory recovery in excitable media, we present a new type of meandering of the spiral waves, which leads to spiral break up and spatiotemporal chaos. The tip of the spiral follows an outward spiral-like trajectory and the spiral core expands in time. This type of destabilization of simple rotation is attributed to the effects of curvature and the wave-fronts interactions in the case of oscillatory damped recovery to the rest state. This model offers a new route to and caricature for cardiac fibrillation, and when we apply the feedback resonant drift method, for defibrillation all wave activity gets eliminated at the unexcitable boundaries.

A quantum computer uses superposition states to accomplish tasks (e.g., database search and factoring of integers) more efficiently than any known classical computing strategy. In conventional registers for quantum information processing, quantum bits are associated with individual two-level quantum systems. Separate addressing and interaction with these systems permit one-bit gates, while an interaction between systems is needed
to accomplish two-bit gates.

The seminar will review recent theoretical proposals to implement quantum computing in collective excitation degrees of freedom in ensembles of
identical quantum systems. In these proposals one does not address individual particles, but one needs a suitable global interaction to perform
quantum logic operations in the system.

Such a global interaction exists in hybrid systems where large ensembles of electron or nuclear spins in a solid are collectively coupled to
superconducting qubit elements via a quantized cavity field. These physical components are optimal for the very different tasks of stable memory and
rapid processing functions, needed in a quantum computer  The main ideas of the spin-ensemble encoding and impressive preliminary proof-of-principle
experiments will be discussed.

A cell is not just a small test tube in which biochemical reactions take place, but it also has a complex and highly dynamic mechanical structure. I will discuss the underlying physical principles that govern cellular mechanics on the nanoscale, and explore how DNA mechanics, on its own and within the context of a heavily crowded, constrained and perpetually fluctuating cellular environment, affects biological function. For example, forces of less than hundred femtonewtons can mechanically switch genes on and off by preventing the formation of regulatory DNA-protein complexes. Special emphasis will be placed on the role of intracellular fluctuations and noise, as our data indicate that active non-equilibrium fluctuations from molecular motor action, as opposed to purely thermal noise, may play a crucial role in efficiently assembling the genetic machinery.

"From Cardiac Cells to Genetic Regulatory Networks"
R. Grosu, G. Batt, F. Fenton, J. Glimm, C. Le Guernic, S.A. Smolka, and E. Bartocci

A fundamental question in the treatment of cardiac disorders, such as tachycardia and fibrillation, is under what circumstances does such a disorder arise? To answer to this question, we develop a multiaffine hybrid automaton (MHA) cardiac-cell model, and restate the original question as one of identication of the parameter ranges under which the MHA model accurately reproduces the disorder. The MHA model is obtained from the minimal cardiac model of Fenton by first bringing it into the form of a canonical, genetic regulatory network, and then linearizing its sigmoidal switches, in an optimal way. By leveraging the Rovergene tool for genetic regulatory networks, we are then able to successfully identify the parameter ranges of interest.

To view and/or participate in the webinar from wherever you are, click on:
evo.caltech.edu/evoNext/koala.jnlp?meeting=MDMaM8292nDIDB999tD99D

Most biological processes are mediated by mediated by protein association, and often are under kinetic rather than thermodynamic control. We have developed the transient-complex theory for protein association, which presents a framework for elucidating the mechanisms of protein association and for predicting the association rates. The transient complex refers to an intermediate along the association process, in which the two associating molecules have near-native separation and relative orientation but have yet to form the short-range specific interactions of the native complex. Our theory rationalizes the variations in association rates over 10 orders of magnitudes and gives accurate prediction of the association rates based on the structures of the native complexes. In the cellular context, association processes occur in the presence of a high concentration of background macromolecules. We have developed methods to model the effects of the crowded cellular environments on the affinities and rate constants of protein association. These studies allow us to achieve a quantitative understanding of biological processes in the cellular context, based on fundamental physical principles.

We all know that modern science is undergoing a profound transformation as it aims to tackle the complex problems of the 21st Century.  It is
becoming highly collaborative; problems as diverse as climate change, renewable energy, or the origin of gamma-ray bursts require understanding
processes that no single group or community alone has the skills to address. At the same time, after centuries of little change, compute, data, and network environments have grown by 9-12 orders of magnitude in the last few decades.  Moreover, science is not only compute-intensive but is dominated now by data-intensive methods.  This dramatic change in the culture and methodology of science will require a much more integrated and comprehensive approach to development and deployment of hardware, software, and algorithmic tools and environments supporting research, education, and increasingly collaboration across disciplines.

Neutron stars are observed to rotate as fast as 716 Hz. Astrophysicists believe that they are spun-up by accretion of matter and angular momentum in binary star systems. However, the "r-mode" instability of rotating neutron stars, which is driven by gravitational radiation reaction, appears to prevent spin up via accretion to rotation frequencies above about 350 Hz.