1,741 research outputs found
Tunable Graphene Antennas for Selective Enhancement of THz-Emission
In this paper, we will introduce THz graphene antennas that strongly enhance
the emission rate of quantum systems at specific frequencies. The tunability of
these antennas can be used to selectively enhance individual spectral features.
We will show as an example that any weak transition in the spectrum of coronene
can become the dominant contribution. This selective and tunable enhancement
establishes a new class of graphene-based THz devices, which will find
applications in sensors, novel light sources, spectroscopy, and quantum
communication devices
Vortex-type elastic structured media and dynamic shielding
The paper addresses a novel model of metamaterial structure. A system of
spinners has been embedded into a two-dimensional periodic lattice system. The
equations of motion of spinners are used to derive the expression for the
chiral term in the equations describing the dynamics of the lattice. Dispersion
of elastic waves is shown to possess innovative filtering and polarization
properties induced by the vortextype nature of the structured media. The
related homogenised effective behavior is obtained analytically and it has been
implemented to build a shielding cloak around an obstacle. Analytical work is
accompanied by numerical illustrations.Comment: 24 pages, 13 figure
Multispace and Multilevel BDDC
BDDC method is the most advanced method from the Balancing family of
iterative substructuring methods for the solution of large systems of linear
algebraic equations arising from discretization of elliptic boundary value
problems. In the case of many substructures, solving the coarse problem exactly
becomes a bottleneck. Since the coarse problem in BDDC has the same structure
as the original problem, it is straightforward to apply the BDDC method
recursively to solve the coarse problem only approximately. In this paper, we
formulate a new family of abstract Multispace BDDC methods and give condition
number bounds from the abstract additive Schwarz preconditioning theory. The
Multilevel BDDC is then treated as a special case of the Multispace BDDC and
abstract multilevel condition number bounds are given. The abstract bounds
yield polylogarithmic condition number bounds for an arbitrary fixed number of
levels and scalar elliptic problems discretized by finite elements in two and
three spatial dimensions. Numerical experiments confirm the theory.Comment: 26 pages, 3 figures, 2 tables, 20 references. Formal changes onl
The prevalence of silent kidney stones: An ultrasonographic screening study
Objective: Silent and not yet discovered stones of the upper urinary tract are potentially dangerous, since in due course they may cause infection, obstruction and renal damage. The aim of this study was to determine the prevalence of such silent kidney stones in a representative Pakistani population of Karachi. Subjects and Methods: We studied 201 consecutive subjects at our hospital who underwent additional kidney screening whilst undergoing abdominal ultrasound. All these subjects did not have a history or symptoms of urolithiasis. Results: We found silent kidney stones in 3% of subjects. All stone bearers were males. Most stones were in the left kidney. Notably, multiple stones and stones of a considerable size went unnoticed. Conclusion: In addition to the usual figures of incidence and prevalence of stone disease drawn from patient data, there is a prevalence of 3% silent stones that may only be discovered incidentally or by screening. This is true for a “stone country” like Pakistan. Figures for other regions have yet to be determined. Due to socioeconomic reasons, we believe that a general kidney screening for urolithiasis is, however, not indicated, at least in our countr
A ferrofluid based neural network: design of an analogue associative memory
We analyse an associative memory based on a ferrofluid, consisting of a
system of magnetic nano-particles suspended in a carrier fluid of variable
viscosity subject to patterns of magnetic fields from an array of input and
output magnetic pads. The association relies on forming patterns in the
ferrofluid during a trainingdphase, in which the magnetic dipoles are free to
move and rotate to minimize the total energy of the system. Once equilibrated
in energy for a given input-output magnetic field pattern-pair the particles
are fully or partially immobilized by cooling the carrier liquid. Thus produced
particle distributions control the memory states, which are read out
magnetically using spin-valve sensors incorporated in the output pads. The
actual memory consists of spin distributions that is dynamic in nature,
realized only in response to the input patterns that the system has been
trained for. Two training algorithms for storing multiple patterns are
investigated. Using Monte Carlo simulations of the physical system we
demonstrate that the device is capable of storing and recalling two sets of
images, each with an accuracy approaching 100%.Comment: submitted to Neural Network
A perfect absorber made of a graphene micro-ribbon metamaterial
Metamaterial-based perfect absorbers promise many applications. Perfect absorption is characterized by the complete suppression of transmission and reflection and complete dissipation of the incident energy by the absorptive meta-atoms. A certain absorption spectrum is usually assigned to a bulk medium and serves as a signature of the respective material. Here we show how to use graphene flakes as building blocks for perfect absorbers. Then, an absorbing meta-atom only consists of a molecular monolayer placed at an appropriate distance from a metallic ground plate. We show that the functionality of such device is intuitively and correctly explained by a Fabry-Perot model
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