5 resultados para Resonant circuits

em Universidade Complutense de Madrid


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One of the main technical difficulties in the fabrication of optical antennas working as light detectors is the proper design and manufacture of auxiliary elements as load lines and signal extraction structures. These elements need to be quite small to reach the location of the antennas and should have a minimal effect on the response of the device. Unfortunately this is not an easy task and signal extraction lines resonate along with the antenna producing a complex signal that usually masks the one given by the antenna. In order to decouple the resonance from the transduction we present in this contribution a parametric analysis of the response of a bolometric stripe that is surrounded by resonant dipoles with different geometries and orientations. We have checked that these elements should provide a signal proportional to the polarization state of the incoming light.

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We introduce a model of a nonlinear double-barrier structure to describe in a simple way the effects of electron-electron scattering while remaining analytically tractable. The model is based on a generalized effective-mass equation where a nonlinear local field interaction is introduced to account for those inelastic scattering phenomena. Resonance peaks seen in the transmission coefficient spectra for the linear case appear shifted to higher energies depending on the magnitude of the nonlinear coupling. Our results are in good agreement with self-consistent solutions of the Schrodinger and Poisson equations. The calculation procedure is seen to be very fast, which makes our technique a good candidate for a rapid approximate analysis of these structures.

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Seebeck nanoantennas, which are based on the thermoelectric effect, have been proposed for electromagnetic energy harvesting and infrared detection. The responsivity and frequency dependence of three types of Seebeck nanoantennas is obtained by electromagnetic simulation for different materials. Results show that the square spiral antenna has the widest bandwidth and the highest induced current of the three analyzed geometries. However, the geometry that presented the highest temperature gradient was the bowtie antenna, which favors the thermoelectric effect in a Seebeck nanoantenna. The results also show that these types of devices can present a voltage responsivity as high as 36  μV/W36  μV/W for titanium–nickel dipoles resonant at far-infrared wavelengths.

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In this paper we present an experimental validation of the reliability increase of digital circuits implemented in XilinxTMFPGAs when they are implemented using the DSPs (Digital Signal Processors) that are available in the reconfigurable device. For this purpose, we have used a fault-injection platform developed by our research group, NESSY [1]. The presented experiments demonstrate that the probability of occurrence of a SEU effect is similar both in the circuits implemented with and without using embedded DSPs. However, the former are more efficient in terms of area usage, which leads to a decrease in the probability of a SEU occurrence.

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The synchronization of oscillatory activity in networks of neural networks is usually implemented through coupling the state variables describing neuronal dynamics. In this study we discuss another but complementary mechanism based on a learning process with memory. A driver network motif, acting as a teacher, exhibits winner-less competition (WLC) dynamics, while a driven motif, a learner, tunes its internal couplings according to the oscillations observed in the teacher. We show that under appropriate training the learner motif can dynamically copy the coupling pattern of the teacher and thus synchronize oscillations with the teacher. Then, we demonstrate that the replication of the WLC dynamics occurs for intermediate memory lengths only. In a unidirectional chain of N motifs coupled through teacher-learner paradigm the time interval required for pattern replication grows linearly with the chain size, hence the learning process does not blow up and at the end we observe phase synchronized oscillations along the chain. We also show that in a learning chain closed into a ring the network motifs come to a consensus, i.e. to a state with the same connectivity pattern corresponding to the mean initial pattern averaged over all network motifs.