89 resultados para Random Walks


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The random distributed feedback fiber laser operating via the stimulated Raman scattering and random distributed feedback based on the Rayleigh scattering is demonstrated in the 1.2 μm frequency band. The RDFB fiber laser generates at 1174 nm up to 2.4 W of output power with corresponding slope efficiency more than 30%. The output radiation has the spectral shape similar to the conventional Raman fiber lasers and spectral width less than 1.7 nm. © 2011 Pleiades Publishing, Ltd.

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We demonstrate a CW random distributed feedback Raman fiber laser operating in a 1.2 μm spectral band. The laser generates up to 3.8 W of the quasi-CW radiation at 1175 nm with the narrow spectrum of 1 nm. Conversion efficiency reaches 60%. Up to 1 W is generated at the second Stokes wavelength of 1242 nm. It is shown that the generation spectrum of RDFB Raman fiber laser is much narrower than the spectrum in the system without a weak random feedback. © 2011 Optical Society of America.

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We demonstrate that a distributed Raman amplification scheme based on random distributed feedback (DFB) fiber laser enables bidirectional second-order Raman pumping without increasing relative intensity noise (RIN) of the signal. This extends the reach of 10 × 116 Gb/s DP-QPSK WDM transmission up to 7915 km, compared with conventional Raman amplification schemes. Moreover, this scheme gives the longest maximum transmission distance among all the Raman amplification schemes presented in this paper, whilst maintaining relatively uniform and symmetric signal power distribution, and is also adjustable in order to be highly compatible with different nonlinearity compensation techniques, including mid-link optical phase conjugation (OPC) and nonlinear Fourier transform (NFT).

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Random fiber lasers blend together attractive features of traditional random lasers, such as low cost and simplicity of fabrication, with high-performance characteristics of conventional fiber lasers, such as good directionality and high efficiency. Low coherence of random lasers is important for speckle-free imaging applications. The random fiber laser with distributed feedback proposed in 2010 led to a quickly developing class of light sources that utilize inherent optical fiber disorder in the form of the Rayleigh scattering and distributed Raman gain. The random fiber laser is an interesting and practically important example of a photonic device based on exploitation of optical medium disorder. We provide an overview of recent advances in this field, including high-power and high-efficiency generation, spectral and statistical properties of random fiber lasers, nonlinear kinetic theory of such systems, and emerging applications in telecommunications and distributed sensing.

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We present first experimental investigation of fast-intensity dynamics of random distributed feedback (DFB) fiber lasers. We found that the laser dynamics are stochastic on a short time scale and exhibit pronounced fluctuations including generation of extreme events. We also experimentally characterize statistical properties of radiation of random DFB fiber lasers. We found that statistical properties deviate from Gaussian and depend on the pump power.

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I will overview our recent results on ultra-long lasers and will discuss the concept of a fiber laser with an open cavity that operates using random distributed feedback provided by Rayleigh scattering amplified through the Raman effect. © 2011 Optical Society of America.

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We numerically optimise in-span signal power asymmetry in advanced Raman amplification schemes, reaching 3% over 62 km SMF, and evaluate its impact on the performance of systems using mid-link OPC using 7 × 15 16QAM Nyquist-spaced WDM-PDM. © 2015 OSA.

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Researchers conducted investigations to demonstrate the advantages of random distributed feedback fiber laser. Random lasers had advantages, such as simple technology that did not require a precise microcavity and low production cost. The properties of their output radiation were special in comparison to those of conventional lasers and they were characterized by complex features in the spatial, spectral, and time domains. The researchers demonstrated a new type of one-dimensional laser with random distributed feedback based on Rayleigh scattering (RS) that was presented in any transparent glass medium due to natural inhomogeneities of refractive index. The cylindrical fiber waveguide geometry provided transverse confinement, while the cavity was open in the longitudinal direction and did not include any regular point-action reflectors.

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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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We demonstrate a fibre laser with a mirrorless cavity that operates via Rayleigh scattering amplified through the Raman effect. The properties of such random distributed feedback laser appear different from those of both traditional random lasers and conventional fibre lasers. ©2010 IEEE.

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In the presented paper, the temporal and statistical properties of a Lyot filter based multiwavelength random DFB fiber laser with a wide flat spectrum, consisting of individual lines, were investigated. It was shown that separate spectral lines forming the laser spectrum have mostly Gaussian statistics and so represent stochastic radiation, but at the same time the entire radiation is not fully stochastic. A simple model, taking into account phenomenological correlations of the lines' initial phases was established. Radiation structure in the experiment and simulation proved to be different, demanding interactions between different lines to be described via a NLSE-based model.

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Light localisation in one-dimensional (1D) randomly disordered medium is usually characterized by randomly distributed resonances with fluctuating transmission values, instead of selectively distributed resonances with close-to-unity transmission values that are needed in real application fields. By a resonance tuning scheme developed recently, opening of favorable resonances or closing of unfavorable resonances are achieved by disorder micro-modification, both on the layered medium and the fibre Bragg grating (FBG) array. And furthermore, it is shown that those disorder-induced resonances are independently tunable. Therefore, selected resonances and arranged light localisation can be achieved via artificial disorder, and thus meet the demand of various application fields.

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In this paper, we develop a new family of graph kernels where the graph structure is probed by means of a discrete-time quantum walk. Given a pair of graphs, we let a quantum walk evolve on each graph and compute a density matrix with each walk. With the density matrices for the pair of graphs to hand, the kernel between the graphs is defined as the negative exponential of the quantum Jensen–Shannon divergence between their density matrices. In order to cope with large graph structures, we propose to construct a sparser version of the original graphs using the simplification method introduced in Qiu and Hancock (2007). To this end, we compute the minimum spanning tree over the commute time matrix of a graph. This spanning tree representation minimizes the number of edges of the original graph while preserving most of its structural information. The kernel between two graphs is then computed on their respective minimum spanning trees. We evaluate the performance of the proposed kernels on several standard graph datasets and we demonstrate their effectiveness and efficiency.

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Random Walk with Restart (RWR) is an appealing measure of proximity between nodes based on graph structures. Since real graphs are often large and subject to minor changes, it is prohibitively expensive to recompute proximities from scratch. Previous methods use LU decomposition and degree reordering heuristics, entailing O(|V|^3) time and O(|V|^2) memory to compute all (|V|^2) pairs of node proximities in a static graph. In this paper, a dynamic scheme to assess RWR proximities is proposed: (1) For unit update, we characterize the changes to all-pairs proximities as the outer product of two vectors. We notice that the multiplication of an RWR matrix and its transition matrix, unlike traditional matrix multiplications, is commutative. This can greatly reduce the computation of all-pairs proximities from O(|V|^3) to O(|delta|) time for each update without loss of accuracy, where |delta| (<<|V|^2) is the number of affected proximities. (2) To avoid O(|V|^2) memory for all pairs of outputs, we also devise efficient partitioning techniques for our dynamic model, which can compute all pairs of proximities segment-wisely within O(l|V|) memory and O(|V|/l) I/O costs, where 1<=l<=|V| is a user-controlled trade-off between memory and I/O costs. (3) For bulk updates, we also devise aggregation and hashing methods, which can discard many unnecessary updates further and handle chunks of unit updates simultaneously. Our experimental results on various datasets demonstrate that our methods can be 1–2 orders of magnitude faster than other competitors while securing scalability and exactness.