Multidimensional Bosonization

Bosonization of degenerate fermions yields insight both into Landau Fermi liquids, and into non-Fermi liquids. We begin our review with a pedagogical introduction to bosonization, emphasizing its applicability in spatial dimensions greater than one. After a brief historical overview, we present the essentials of the method. Well known results of Landau theory are recovered, demonstrating that this new tool of many-body theory is robust. Limits of multidimensional bosonization are tested by considering several examples of non-Fermi liquids, in particular the composite fermion theory of the half-filled Landau level. Nested Fermi surfaces present a different challenge, and these may be relevant in the cuprate superconductors. We conclude by discussing the future of multidimensional bosonization.Comment: 91 pages, 15 eps figures, LaTeX. Minor changes to match the published versio

Orientational Melting in Carbon Nanotube Ropes

Using Monte Carlo simulations, we investigate the possibility of an orientational melting transition within a "rope" of (10,10) carbon nanotubes. When twisting nanotubes bundle up during the synthesis, orientational dislocations or twistons arise from the competition between the anisotropic inter-tube interactions, which tend to align neighboring tubes, and the torsion rigidity that tends to keep individual tubes straight. We map the energetics of a rope containing twistons onto a lattice gas model and find that the onset of a free "diffusion" of twistons, corresponding to orientational melting, occurs at T_OM > 160 K.Comment: 4 page LaTeX file with 3 figures (10 PostScript files

Anomalous double peak structure in Nb/Ni superconductor/ferromagnet tunneling DOS

We have experimentally investigated the density of states (DOS) in Nb/Ni (S/F) bilayers as a function of Ni thickness, $d_F$. Our thinnest samples show the usual DOS peak at $\pm\Delta_0$, whereas intermediate-thickness samples have an anomalous ``double-peak'' structure. For thicker samples ($d_F \geq 3.5$ nm), we see an ``inverted'' DOS which has previously only been reported in superconductor/weak-ferromagnet structures. We analyze the data using the self-consistent non-linear Usadel equation and find that we are able to quantitatively fit the features at $\pm\Delta_0$ if we include a large amount of spin-orbit scattering in the model. Interestingly, we are unable to reproduce the sub-gap structure through the addition of any parameter(s). Therefore, the observed anomalous sub-gap structure represents new physics beyond that contained in the present Usadel theory.Comment: 4 pages, 3 figure

An Activity-Based Nanosensor for Traumatic Brain Injury.

Currently, traumatic brain injury (TBI) is detected by medical imaging; however, medical imaging requires expensive capital equipment, is time- and resource-intensive, and is poor at predicting patient prognosis. To date, direct measurement of elevated protease activity has yet to be utilized to detect TBI. In this work, we engineered an activity-based nanosensor for TBI (TBI-ABN) that responds to increased protease activity initiated after brain injury. We establish that a calcium-sensitive protease, calpain-1, is active in the injured brain hours within injury. We then optimize the molecular weight of a nanoscale polymeric carrier to infiltrate into the injured brain tissue with minimal renal filtration. A calpain-1 substrate that generates a fluorescent signal upon cleavage was attached to this nanoscale polymeric carrier to generate an engineered TBI-ABN. When applied intravenously to a mouse model of TBI, our engineered sensor is observed to locally activate in the injured brain tissue. This TBI-ABN is the first demonstration of a sensor that responds to protease activity to detect TBI

Charge and Orbital Ordering and Spin State Transition Driven by Structural Distortion in YBaCo_2O_5

We have investigated electronic structures of antiferromagnetic YBaCo_2O_5 using the local spin-density approximation (LSDA) + U method. The charge and orbital ordered insulating ground state is correctly obtained with the strong on-site Coulomb interaction. Co^{2+} and Co^{3+} ions are found to be in the high spin (HS) and intermediate spin (IS) state, respectively. It is considered that the tetragonal to orthorhombic structural transition is responsible for the ordering phenomena and the spin states of Co ions. The large contribution of the orbital moment to the total magnetic moment indicates that the spin-orbit coupling is also important in YBaCo_2O_5.Comment: 4 pages including 4 figures, Submitted to Phys. Rev. Let

Astronomy in the Cloud: Using MapReduce for Image Coaddition

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection and classification, and moving object tracking. Since such studies benefit from the highest quality data, methods such as image coaddition (stacking) will be a critical preprocessing step prior to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources or transient objects, these data streams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this paper we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data is partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources, e.g., Amazon's EC2. We report on our experience implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multi-terabyte imaging dataset provides a good testbed for algorithm development since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image coaddition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results comparing their performance.Comment: 31 pages, 11 figures, 2 table