103,726 research outputs found
Canonical Formalism for Lagrangians of Maximal Nonlocality
A canonical formalism for Lagrangians of maximal nonlocality is established.
The method is based on the familiar Legendre transformation to a new function
which can be derived from the maximally nonlocal Lagrangian. The corresponding
canonical equations are derived through the standard procedure in local theory
and appear much like those local ones, though the implication of the equations
is largely expanded.Comment: 17 pages with 1 eps figur
Extending the Energy Framework for Network Simulator 3 (ns-3)
The problem of designing and simulating optimal transmission protocols for
energy harvesting wireless networks has recently received considerable
attention, thus requiring for an accurate modeling of the energy harvesting
process and a consequent redesign of the simulation framework to include it.
While the current ns-3 energy framework allows the definition of new energy
sources that incorporate the contribution of an energy harvester, the
integration of an energy harvester component into an existing energy source is
not straightforward using the existing energy framework. In this poster, we
propose an extension of the energy framework currently released with ns-3 in
order to explicitly introduce the concept of an energy harvester. Starting from
the definition of the general interface, we then provide the implementation of
two simple models for the energy harvester. In addition, we extend the set of
implementations of the current energy framework to include a model for a
supercapacitor energy source and a device energy model for the energy
consumption of a sensor. Finally, we introduce the concept of an energy
predictor, that gathers information from the energy source and harvester and
use this information to predict the amount of energy that will be available in
the future, and we provide an example implementation. As a result of these
efforts, we believe that our contributions to the ns-3 energy framework will
provide a useful tool to enhance the quality of simulations of energy-aware
wireless networks.Comment: 2 pages, 4 figures. Poster presented at WNS3 2014, Atlanta, G
Direction-of-Arrival Estimation Based on Sparse Recovery with Second-Order Statistics
Traditional direction-of-arrival (DOA) estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC) sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC) has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS) algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal
Solutions to the Jaynes-Cummings model without the rotating-wave approximation
By using extended bosonic coherent states, the solution to the
Jaynes-Cummings model without the rotating-wave approximation can be mapped to
that of a polynomial equation with a single variable. The solutions to this
polynomial equation can give all eigenvalues and eigenfunctions of this model
with all values of the coupling strength and the detuning exactly, which can be
readily applied to recent circuit quantum electrodynamic systems operating in
the ultra-strong coupling regime.Comment: 6 pages,3 figure
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