103,726 research outputs found

    Canonical Formalism for Lagrangians of Maximal Nonlocality

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    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)

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    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

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    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 ell1ell_1 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

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    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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