Non-Gaussian Resistance Noise near Electrical Breakdown in Granular Materials

The distribution of resistance fluctuations of conducting thin films with granular structure near electrical breakdown is studied by numerical simulations. The film is modeled as a resistor network in a steady state determined by the competition between two biased processes, breaking and recovery. Systems of different sizes and with different levels of internal disorder are considered. Sharp deviations from a Gaussian distribution are found near breakdown and the effect increases with the degree of internal disorder. However, we show that in general this non-Gaussianity is related to the finite size of the system and vanishes in the large size limit. Nevertheless, near the critical point of the conductor-insulator transition, deviations from Gaussianity persist when the size is increased and the distribution of resistance fluctuations is well fitted by the universal Bramwell-Holdsworth-Pinton distribution.Comment: 8 pages, 6 figures; accepted for publication on Physica

Statistics of Extreme Values in Time Series with Intermediate-Term Correlations

It will be discussed the statistics of the extreme values in time series characterized by finite-term correlations with non-exponential decay. Precisely, it will be considered the results of numerical analyses concerning the return intervals of extreme values of the fluctuations of resistance and defect-fraction displayed by a resistor with granular structure in a nonequilibrium stationary state. The resistance and defect-fraction are calculated as a function of time by Monte Carlo simulations using a resistor network approach. It will be shown that when the auto-correlation function of the fluctuations displays a non-exponential and non-power-law decay, the distribution of the return intervals of extreme values is a stretched exponential, with exponent largely independent of the threshold. Recently, a stretched exponential distribution of the return intervals of extreme values has been identified in long-term correlated time series by Bunde et al. (2003) and Altmann and Kantz (2005). Thus, the present results show that the stretched exponential distribution of the return intervals is not an exclusive feature of long-term correlated time series.Comment: 6 pages, 7 figures, conference paper, in Noise and Stochastics in Complex Systems and Finance, ed. by J. Kertez, S. Bornhold, R. N. Mantegna, Procs. of SPIE, vol. 6601, 19, 200

Distribution of Return Intervals of Extreme Events

The distribution of return intervals of extreme events is studied in time series characterized by finite-term correlations with non-exponential decay. Precisely, it has been analyzed the statistics of the return intervals of extreme values of the resistance fluctuations displayed by resistors with granular structure in nonequilibrium stationary states. The resistance fluctuations are calculated by Monte Carlo simulations using a resistor network approach. It has been found that for highly disordered networks, when the auto-correlation function displays a non-exponential and non-power-law decay, the distribution of return intervals of the extreme values is a stretched exponential, with exponent independent of the threshold.Comment: 10 pages, 6 figures, Next-SigmaPhi Int. Conference, News Expectations and Trends in Statistical Physics, 13-18 August 2005, Kolymbari - Crete (Greece

Distribution of Return Periods of Rare Events in Correlated Time Series

We study the effect on the distribution of return periods of rare events of the presence in a time series of finite-term correlations with non-exponential decay. Precisely, we analyze the auto-correlation function and the statistics of the return intervals of extreme values of the resistance fluctuations displayed by a resistor with granular structure in a nonequilibrium stationary state. The resistance fluctuations, $\delta R$, are calculated by Monte Carlo simulations using the SBRN model introduced some years ago by Pennetta, Tref\'an and Reggiani and based on a resistor network approach. A rare event occurs when $\delta R$ overcomes a threshold value $q$ significantly higher than the average value of the resistance. We have found that for highly disordered networks, when the auto-correlation function displays a non-exponential decay but yet the resistance fluctuations are characterized by a finite correlation time, the distribution of return intervals of the extreme values is well described by a stretched exponential, with exponent largely independent of the threshold $q$. We discuss this result and some of the main open questions related to it, also in connection with very recent findings by other authors concerning the observation of stretched exponential distributions of return intervals of extreme events in long-term correlated time series.Comment: 10 pages, 8 figures, Procs. of 4th. Int. Conf. on Unsolved Problems on Noise and Fluctuations in Physics, Biology and High Technology (UPoN05), 6-10 June 2005, Gallipoli (Italy), AIP Conf. Procs. (in print

Trapping-detrapping fluctuations in organic space-charge layers

A trapping-detrapping model is proposed for explaining the current fluctuation behavior in organic semiconductors (polyacenes) operating under current-injection conditions. The fraction of ionized traps obtained from the current-voltage characteristics, is related to the relative current noise spectral density at the trap-filling transition. The agreement between theory and experiments validates the model and provides an estimate of the concentration and energy level of deep traps

A Percolative Model of Soft Breakdown in Ultrathin Oxides

The degradation of ultrathin oxide layers in the presence of a stress voltage is modeled in terms of two antagonist percolation processes taking place in a random resistor network. The resistance and leakage current fluctuations are studied by MonteCarlo simulations for voltages below the breakdown threshold. An increase of excess noise together with a noticeable non-Gaussian behavior is found in the pre-breakdown regime in agreement with experimental results.Comment: accepted for publication on Physica

Universality and Scaling Behaviour of Injected Power in Elastic Turbulence in Worm-like Micellar Gel

We study the statistical properties of spatially averaged global injected power fluctuations for Taylor-Couette flow of a worm-like micellar gel formed by surfactant CTAT. At sufficiently high Weissenberg numbers (Wi) the shear rate and hence the injected power p(t) at a constant applied stress shows large irregular fluctuations in time. The nature of the probability distribution function (pdf) of p(t) and the power-law decay of its power spectrum are very similar to that observed in recent studies of elastic turbulence for polymer solutions. Remarkably, these non-Gaussian pdfs can be well described by an universal large deviation functional form given by the Generalized Gumbel (GG) distribution observed in the context of spatially averaged global measures in diverse classes of highly correlated systems. We show by in-situ rheology and polarized light scattering experiments that in the elastic turbulent regime the flow is spatially smooth but random in time, in agreement with a recent hypothesis for elastic turbulence.Comment: 8 pages, 3 figure