986 resultados para random lasing


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As shown recently, a long telecommunication fibre may be treated as a natural one-dimensional random system, where lasing is possible due to a combination of random distributed feedback via Rayleigh scattering by natural refractive index inhomogeneities and distributed amplification through the Raman effect. Here we present a new type of a random fibre laser with a narrow (∼1 nm) spectrum tunable over a broad wavelength range (1535-1570 nm) with a uniquely flat (∼0.1 dB) and high (>2 W) output power and prominent (>40 %) differential efficiency, which outperforms traditional fibre lasers of the same category, e.g. a conventional Raman laser with a linear cavity formed in the same fibre by adding point reflectors. Analytical model is proposed that explains quantitatively the higher efficiency and the flatter tuning curve of the random fiber laser compared to conventional one. The other important features of the random fibre laser like "modeless" spectrum of specific shape and corresponding intensity fluctuations as well as the techniques of controlling its output characteristics are discussed. Outstanding characteristics defined by new underlying physics and the simplicity of the scheme implemented in standard telecom fibre make the demonstrated tunable random fibre laser a very attractive light source both for fundamental science and practical applications such as optical communication, sensing and secure transmission. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

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The longitudinal distribution of the Stokes-component power in a Raman fibre laser with a random distributed feedback and unidirectional pumping is measured. The fibre parameters (linear loss and Rayleigh backscattering coefficient) are calculated based on the distributions obtained. A numerical model is developed to describe the lasing power distribution. The simulation results are in good agreement with the experimental data. © 2012 Kvantovaya Elektronika and Turpion Ltd.

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Recently, the concept of a random distributed feedback (DFB) lasing in optical fibers has been demonstrated [1], A number of different random DFB fiber lasers has been demonstrated so far including tunable, multiwalength, cascaded generation, generation in different spectral bands etc [2-7]. All systems are based on standard low-loss germanium doped silica core fibres having relatively low Rayleigh scattering coefficient. Thus, the typical length of random DFB fiber lasers is in the range from several kilometres to tens of kilometres to accumulate enough random feedback. Here we demonstrate for the first time to our knowledge the random DFB fiber laser based on a nitrogen doped silica core (N-doped) fiber. The fiber has several times higher Rayleigh scattering coefficient compared to standard telecommunication fibres. Thus, the generation is achieved in 500 meters long fiber only. © 2013 IEEE.

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We demonstrate lasing based on a random distributed feedback due to the Raman amplified Rayleigh backscattering in different types of cavities with and without conventional point-action reflectors. Quasistationary generation of a narrowband spectrum is achieved despite the random nature of the feedback. The generated spectrum is localized at the reflection or gain spectral maxima in schemes with and without point reflectors, respectively. The length limit for a conventional cavity and the minimal pump power required for the lasing based purely on a random distributed feedback are determined. © 2010 The American Physical Society.

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Channel measurements and simulations have been carried out to observe the effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity. An in-house built MIMO-OFDM packet transmission demonstrator equipped with four transmitters and four receivers has been utilized to perform channel measurements at 5.2 GHz. Variations in the channel capacity dynamic range have been analysed for 1 to 10 pedestrians and different antenna arrays (2 × 2, 3 × 3 and 4 × 4). Results show a predicted 5.5 bits/s/Hz and a measured 1.5 bits/s/Hz increment in the capacity dynamic range with the number of pedestrian and the number of antennas in the transmitter and receiver array.

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Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

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In this paper, we consider a time-space fractional diffusion equation of distributed order (TSFDEDO). The TSFDEDO is obtained from the standard advection-dispersion equation by replacing the first-order time derivative by the Caputo fractional derivative of order α∈(0,1], the first-order and second-order space derivatives by the Riesz fractional derivatives of orders β 1∈(0,1) and β 2∈(1,2], respectively. We derive the fundamental solution for the TSFDEDO with an initial condition (TSFDEDO-IC). The fundamental solution can be interpreted as a spatial probability density function evolving in time. We also investigate a discrete random walk model based on an explicit finite difference approximation for the TSFDEDO-IC.

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This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.

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In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.