48 resultados para LAST PASSAGE PERCOLATION


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The aim of this article is to analyze accurately the role played by two classical references, Venus and Oedipus, in Tennessee Williams¿s Suddenly Last Summer, in accordance with the usual nature of studies on Classical Tradition ¿Greek and Roman- and focusing in this case on the relationship between literature and mythology. It is thanks to Venus and Oedipus that the playwright succeeds in showing the magnitude of men¿s and women¿s tragedy, which from his point of view is simply that they have failed to see either kindness in the face of God or to feel his loving and fatherly providence.

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The aim of this article is to analyze accurately the role played by two classical references, Venus and Oedipus, in Tennessee Williams Suddenly Last Summer, in accordance with the usual nature of studies on Classical Tradition a Greek and Roman- and focusing in this case on the relationship between literature and mythology. It is thanks to Venus and Oedipus that the playwright succeeds in showing the magnitude of mens and womens tragedy, which from his point of view is simply that they have failed to see either kindness in the face of God or to feel his loving and fatherly providence.

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The aim of this article is to analyze accurately the role played by two classical references, Venus and Oedipus, in Tennessee Williams's Suddenly Last Summer, in accordance with the usual nature of studies on Classical Tradition -Greek and Roman- and focusing in this case on the relationship between literature and mythology. It is thanks to Venus and Oedipus that the playwright succeeds in showing the magnitude of men¿s and women¿s tragedy, which from his point of view is simply that they have failed to see either kindness in the face of God or to feel his loving and fatherly providence.

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First-passage time statistics for non-Markovian processes have heretofore only been developed for processes driven by dichotomous fluctuations that are themselves Markov. Herein we develop a new method applicable to Markov and non-Markovian dichotomous fluctuations and calculate analytic mean first-passage times for particular examples.

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We develop a method to obtain first-passage-time statistics for non-Markovian processes driven by dichotomous fluctuations. The fluctuations themselves need not be Markovian. We calculate analytic first-passage-time distributions and mean first-passage times for exponential, rectangular, and long-tail temporal distributions of the fluctuations.

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Our previously developed stochastic trajectory analysis technique has been applied to the calculation of first-passage time statistics of bound processes. Explicit results are obtained for linearly bound processes driven by dichotomous fluctuations having exponential and rectangular temporal distributions.

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Herein we present a calculation of the mean first-passage time for a bistable one-dimensional system driven by Gaussian colored noise of strength D and correlation time ¿c. We obtain quantitative agreement with experimental analog-computer simulations of this system. We disagree with some of the conclusions reached by previous investigators. In particular, we demonstrate that all available approximations that lead to a state-dependent diffusion coefficient lead to the same result for small D¿c.

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The stochastic-trajectory-analysis technique is applied to the calculation of the mean¿first-passage-time statistics for processes driven by external shot noise. Explicit analytical expressions are obtained for free and bound processes.

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A new method for the calculation of first-passage times for non-Markovian processes is presented. In addition to the general formalism, some familiar examples are worked out in detail.

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We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant connected component, it cannot restore a finite percolation threshold. In turn, this implies the absence of an epidemic threshold in this class of networks, thus extending this result to a wide variety of real scale-free networks which shows a high level of transitivity. Our findings are in good agreement with numerical simulations.

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We consider a Potts model diluted by fully frustrated Ising spins. The model corresponds to a fully frustrated Potts model with variables having an integer absolute value and a sign. This model presents precursor phenomena of a glass transition in the high-temperature region. We show that the onset of these phenomena can be related to a thermodynamic transition. Furthermore, this transition can be mapped onto a percolation transition. We numerically study the phase diagram in two dimensions (2D) for this model with frustration and without disorder and we compare it to the phase diagram of (i) the model with frustration and disorder and (ii) the ferromagnetic model. Introducing a parameter that connects the three models, we generalize the exact expression of the ferromagnetic Potts transition temperature in 2D to the other cases. Finally, we estimate the dynamic critical exponents related to the Potts order parameter and to the energy.

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We calculate noninteger moments ¿tq¿ of first passage time to trapping, at both ends of an interval (0,L), for some diffusion and dichotomous processes. We find the critical behavior of ¿tq¿, as a function of q, for free processes. We also show that the addition of a potential can destroy criticality.

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A general scheme for devising efficient cluster dynamics proposed in a previous paper [Phys. Rev. Lett. 72, 1541 (1994)] is extensively discussed. In particular, the strong connection among equilibrium properties of clusters and dynamic properties as the correlation time for magnetization is emphasized. The general scheme is applied to a number of frustrated spin models and the results discussed.

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We develop a general theory for percolation in directed random networks with arbitrary two-point correlations and bidirectional edgesthat is, edges pointing in both directions simultaneously. These two ingredients alter the previously known scenario and open new views and perspectives on percolation phenomena. Equations for the percolation threshold and the sizes of the giant components are derived in the most general case. We also present simulation results for a particular example of uncorrelated network with bidirectional edges confirming the theoretical predictions.

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We numerically study the dynamical properties of fully frustrated models in two and three dimensions. The results obtained support the hypothesis that the percolation transition of the Kasteleyn-Fortuin clusters corresponds to the onset of stretched exponential autocorrelation functions in systems without disorder. This dynamical behavior may be due to the large scale effects of frustration, present below the percolation threshold. Moreover, these results are consistent with the picture suggested by Campbell et al. [J. Phys. C 20, L47 (1987)] in the space of configurations.