Frequency shift keying in vortex-based spin torque oscillators

Vortex-based spin-torque oscillators can be made from extended spin valves connected to an electrical nanocontact. We study the implementation of frequency shift keying modulation in these oscillators. Upon a square modulation of the current in the 10 MHz range, the vortex frequency follows the current command, with easy identification of the two swapping frequencies in the spectral measurements. The frequency distribution of the output power can be accounted for by convolution transformations of the dc current vortex waveform, and the current modulation. Modeling indicates that the frequency transitions are phase coherent and last less than 25 ns. Complementing the multi-octave tunability and first-class agility, the capability of frequency shift keying modulation is an additional milestone for the implementation of vortex-based oscillators in RF circuit.Comment: 6 pages, 5 figure

Back-hopping in Spin-Transfer-Torque switching of perpendicularly magnetized tunnel junctions

We analyse the phenomenon of back-hopping in spin-torque induced switching of the magnetization in perpendicularly magnetized tunnel junctions. The analysis is based on single-shot time-resolved conductance measurements of the pulse-induced back-hopping. Studying several material variants reveals that the back-hopping is a feature of the nominally fixed system of the tunnel junction. The back-hopping is found to proceed by two sequential switching events that lead to a final state P' of conductance close to --but distinct from-- that of the conventional parallel state. The P' state does not exist at remanence. It generally relaxes to the conventional antiparallel state if the current is removed. The P' state involves a switching of the sole spin-polarizing part of the fixed layers. The analysis of literature indicates that back-hopping occurs only when the spin-polarizing layer is too weakly coupled to the rest of the fixed system, which justifies a posteriori the mitigation strategies of back-hopping that were implemented empirically in spin-transfer-torque magnetic random access memories.Comment: submitted to Phys Rev.

Comparison among five hydrodynamic codes with a diverging-converging nozzle experiment

A realistic open-cycle gas-core nuclear rocket simulation model must be capable of a self-consistent nozzle calculation in conjunction with coupled radiation and neutron transport in three spatial dimensions. As part of the development effort for such a model, five hydrodynamic codes were used to compare with a converging-diverging nozzle experiment. The codes used in the comparison are CHAD, FLUENT, KIVA2, RAMPANT, and VNAP2. Solution accuracy as a function of mesh size is important because, in the near term, a practical three-dimensional simulation model will require rather coarse zoning across the nozzle throat. In the study, four different grids were considered. (1) coarse, radially uniform grid, (2) coarse, radially nonuniform grid, (3) fine, radially uniform grid, and (4) fine, radially nonuniform grid. The study involves code verification, not prediction. In other words, the authors know the solution they want to match, so they can change methods and/or modify an algorithm to best match this class of problem. In this context, it was necessary to use the higher-order methods in both FLUENT and RAMPANT. In addition, KIVA2 required a modification that allows significantly more accurate solutions for a converging-diverging nozzle. From a predictive point of view, code accuracy with no tuning is an important result. The most accurate codes on a coarse grid, CHAD and VNAP2, did not require any tuning. Their main comparison among the codes was the radial dependence of the Mach number across the nozzle throat. All five codes yielded a very similar solution with fine, radially uniform and radially nonuniform grids. However, the codes yielded significantly different solutions with coarse, radially uniform and radially nonuniform grids. For all the codes, radially nonuniform zoning across the throat significantly increased solution accuracy with a coarse mesh. None of the codes agrees in detail with the weak shock located downstream of the nozzle throat, but all the codes indicated the presence of a weak downstream shock

Gradient methods for problems with inexact model of the objective

We consider optimization methods for convex minimization problems under inexact information on the objective function. We introduce inexact model of the objective, which as a particular cases includes inexact oracle [19] and relative smoothness condition [43]. We analyze gradient method which uses this inexact model and obtain convergence rates for convex and strongly convex problems. To show potential applications of our general framework we consider three particular problems. The first one is clustering by electorial model introduced in [49]. The second one is approximating optimal transport distance, for which we propose a Proximal Sinkhorn algorithm. The third one is devoted to approximating optimal transport barycenter and we propose a Proximal Iterative Bregman Projections algorithm. We also illustrate the practical performance of our algorithms by numerical experiments

Advances in low-memory subgradient optimization

One of the main goals in the development of non-smooth optimization is to cope with high dimensional problems by decomposition, duality or Lagrangian relaxation which greatly reduces the number of variables at the cost of worsening differentiability of objective or constraints. Small or medium dimensionality of resulting non-smooth problems allows to use bundle-type algorithms to achieve higher rates of convergence and obtain higher accuracy, which of course came at the cost of additional memory requirements, typically of the order of n2, where n is the number of variables of non-smooth problem. However with the rapid development of more and more sophisticated models in industry, economy, finance, et all such memory requirements are becoming too hard to satisfy. It raised the interest in subgradient-based low-memory algorithms and later developments in this area significantly improved over their early variants still preserving O(n) memory requirements. To review these developments this chapter is devoted to the black-box subgradient algorithms with the minimal requirements for the storage of auxiliary results, which are necessary to execute these algorithms. To provide historical perspective this survey starts with the original result of N.Z. Shor which opened this field with the application to the classical transportation problem. The theoretical complexity bounds for smooth and non-smooth convex and quasi-convex optimization problems are briefly exposed in what follows to introduce to the relevant fundamentals of non-smooth optimization. Special attention in this section is given to the adaptive step-size policy which aims to attain lowest complexity bounds. Unfortunately the non-differentiability of objective function in convex optimization essentially slows down the theoretical low bounds for the rate of convergence in subgradient optimization compared to the smooth case but there are different modern techniques that allow to solve non-smooth convex optimization problems faster then dictate lower complexity bounds. In this work the particular attention is given to Nesterov smoothing technique, Nesterov Universal approach, and Legendre (saddle point) representation approach. The new results on Universal Mirror Prox algorithms represent the original parts of the survey. To demonstrate application of non-smooth convex optimization algorithms for solution of huge-scale extremal problems we consider convex optimization problems with non-smooth functional constraints and propose two adaptive Mirror Descent methods. The first method is of primal-dual variety and proved to be optimal in terms of lower oracle bounds for the class of Lipschitz-continuous convex objective and constraints. The advantages of application of this method to sparse Truss Topology Design problem are discussed in certain details. The second method can be applied for solution of convex and quasi-convex optimization problems and is optimal in a sense of complexity bounds. The conclusion part of the survey contains the important references that characterize recent developments of non-smooth convex optimization

Transparent Meta-Analysis of Prospective Memory and Aging

Prospective memory (ProM) refers to our ability to become aware of a previously formed plan at the right time and place. After two decades of research on prospective memory and aging, narrative reviews and summaries have arrived at widely different conclusions. One view is that prospective memory shows large age declines, larger than age declines on retrospective memory (RetM). Another view is that prospective memory is an exception to age declines and remains invariant across the adult lifespan. The present meta-analysis of over twenty years of research settles this controversy. It shows that prospective memory declines with aging and that the magnitude of age decline varies by prospective memory subdomain (vigilance, prospective memory proper, habitual prospective memory) as well as test setting (laboratory, natural). Moreover, this meta-analysis demonstrates that previous claims of no age declines in prospective memory are artifacts of methodological and conceptual issues afflicting prior research including widespread ceiling effects, low statistical power, age confounds, and failure to distinguish between various subdomains of prospective memory (e.g., vigilance and prospective memory proper)

Architecture and Gender : Lessons from Building Archaeology in Africa

Peer reviewe

Immunocompetent 3D Model of Human Upper Airway for Disease Modeling and In Vitro Drug Evaluation

The development of more complex in vitro models for the assessment of novel drugs and chemicals is needed because of the limited biological relevance of animal models to humans as well as ethical considerations. Although some human-cell-based assays exist, they are usually 2D, consist of single cell type, and have limited cellular and functional representation of the native tissue. In this study, we have used biomimetic porous electrospun scaffolds to develop an immunocompetent 3D model of the human respiratory tract comprised of three key cell types present in upper airway epithelium. The three cell types, namely, epithelial cells (providing a physical barrier), fibroblasts (extracellular matrix production), and dendritic cells (immune sensing), were initially grown on individual scaffolds and then assembled into the 3D multicell tissue model. The epithelial layer was cultured at the air–liquid interface for up to four weeks, leading to formation of a functional barrier as evidenced by an increase in transepithelial electrical resistance (TEER) and tight junction formation. The response of epithelial cells to allergen exposure was monitored by quantifying changes in TEER readings and by assessment of cellular tight junctions using immunostaining. It was found that epithelial cells cocultured with fibroblasts formed a functional epithelial barrier at a quicker rate than single cultures of epithelial cells and that the recovery from allergen exposure was also more rapid. Also, our data show that dendritic cells within this model remain viable and responsive to external stimulation as evidenced by their migration within the 3D construct in response to allergen challenge. This model provides an easy to assemble and physiologically relevant 3D model of human airway epithelium that can be used for studies aiming at better understanding lung biology, the cross-talk between immune cells, and airborne allergens and pathogens as well as drug delivery