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 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

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

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

The role of topology in electrical properties of bacteriorhodopsin and rat olfactory receptor I7

We report on electrical properties of the two sensing proteins: bacteriorhodopsin and rat olfactory receptor OR-I7. As relevant transport parameters we consider the small-signal impedance spectrum and the static current-voltage characteristics. Calculations are compared with available experimental results and the model predictability is tested for future perspectives.Comment: 4 pages, 4 figure

Non-Gaussianity of resistance fluctuations near electrical breakdown

We study the resistance fluctuation distribution of a thin film near electrical breakdown. The film is modeled as a stationary resistor networkunder biased percolation. Depending on the value of the external current,on the system sizes and on the level of internal disorder, the fluctuation distribution can exhibit a non-Gaussian behavior. We analyze this non-Gaussianity in terms of the generalized Gumbel distribution recently introduced in the context of highly correlated systems near criticality. We find that when the average fraction of defects approaches the random percolation threshold, the resistance fluctuation distribution is well described by the universal behavior of the Bramwell-Holdsworth-Pinton distribution.Comment: 3 figures, accepted for publication on Semicond Sci Tec

Fluctuations of Complex Networks: Electrical Properties of Single Protein Nanodevices

We present for the first time a complex network approach to the study of the electrical properties of single protein devices. In particular, we consider an electronic nanobiosensor based on a G-protein coupled receptor. By adopting a coarse grain description, the protein is modeled as a complex network of elementary impedances. The positions of the alpha-carbon atoms of each amino acid are taken as the nodes of the network. The amino acids are assumed to interact electrically among them. Consequently, a link is drawn between any pair of nodes neighboring in space within a given distance and an elementary impedance is associated with each link. The value of this impedance can be related to the physical and chemical properties of the amino acid pair and to their relative distance. Accordingly, the conformational changes of the receptor induced by the capture of the ligand, are translated into a variation of its electrical properties. Stochastic fluctuations in the value of the elementary impedances of the network, which mimic different physical effects, have also been considered. Preliminary results concerning the impedance spectrum of the network and its fluctuations are presented and discussed for different values of the model parameters.Comment: 16 Pages and 10 Figures published in SPIE Proceedings of the II International Symposium on Fluctuation and Noise, Maspalomas,Gran Canaria,Spain, 25-28 May 200