Fluctuation and Noise Letters

It is already known that two simple losing games can derive a winning game when randomly combined. This special behaviour is known as Parrondo's Paradox, or the Parrondo effect. In this paper we estimate the volume of the parameter space that determines the Parrondo effect. In other words, how often two randomly chosen games are losing while their proper combination is leading to a winning game. Results for a typical class of relevant games indicate that the Parrondo effect is very unusual, because it appears with a probability of 0.0306%. By adding two more dimensions to the parameter space, the family of regions that exhibit the Parrondo effect is studied.

We discuss the possibility that vacuum fluctuations underlying dark energy could lead to measurable effects for the quantum noise spectrum in Josephson junctions [C. Beck, M. C. Mackey, Phys. Lett. B605, 295 (2005)]. We argue that a recent discussion of Jetzer and Straumann [Phys. Lett. B606, 77 (2005)] relating the measured noise spectrum in Josephson junctions to van der Waals forces is incorrect. The measured noise spectrum in Josephson junctions is a consequence of the fluctuation dissipation theorem and the Josephson effect and has nothing to do with van der Waals forces. Consequently, the argument of Jetzer and Straumann does not shed any light on whether dark energy can or cannot be measured using superconducting Josephson devices. We also point out that a more recent paper of Jetzer and Straumann [Phys. Lett. B639, 57 (2006)] claiming that 'zeropoint energies do not not show up in any application of the fluctuation dissipation theorem' violates the standard view on the subject.

Conductance fluctuations are easily probed by passing a constant current through a pair of driver electrodes and measuring the voltage fluctuations across a pair of sensor electrodes. We calculate the geometrical factor for these fluctuations from the current distribution derived by conformal transformations. In four-electrode configurations on a flat square sample this factor depends only slightly on electrode size, whereas a strong dependence is found for two-electrode configurations. The calculations also give accurate values for the resistance, which allows a comparison with the thermal noise.

The melting of an ultrathin lubricant film is studied at friction between atomically flat surfaces. We take into account fluctuations of lubricant temperature, which are defined by the Ornstein-Uhlenbeck process. Phase diagrams and portraits are calculated for second- and first-order transitions (the melting of an amorphous and that of a crystalline lubricants, respectively). It is shown that, in the former case, a stick-slip friction domain, separating the regions of dry and sliding friction, appears. In the latter case, three domains of stick-slip friction arise, which are characterized by the transitions between dry, metastable and stable sliding friction. The increase in the correlation time of lubricant temperature fluctuations leads to increasing in the rubbing-surface temperature needed for realization of sliding friction. The stationary states, corresponding to dry, stable and metastable sliding friction, are reached as a result of damped oscillations.

The regularity of heart rates has a loss in cases of illness and aging. Assessing the dynamics of heart rate fluctuations can provide valuable information about cardiac system. In this paper, heart rate fluctuations and its wavelet entropy (WE) are analyzed to demonstrate its potentials for risk stratification of cardiac diseases. The regularity of heart rate fluctuations is estimated by exploiting the time-frequency localization ability of wavelet analysis and the ability of entropy. The results show that WE for patients with congestive heart failure show a very low value and can be completely separated from health subjects. In addition, the values of WE decrease with aging. The lower the values of WE, the higher the risk of heart disease is. The values of WE also reflect the distribution of the energy of heart rhythm. Significant correlations are demonstrated between WE and the power in the three frequency bands. The results have shown that WE can be used to analyze short, non-stationary data time series both in time domain and in frequency domain simultaneously and can be feasible for the discrimination of the differences of heart rate fluctuations between healthy groups and CHF groups as a diagnostic tool.

The spectral analysis of electrocardiogram (ECG) and blood pressure fluctuations is an important tool both in medical diagnostics and in theories that endeavour to account for the complex, feedbacked patterns of control mechanisms that regulate human circulation. In the case of ECG signals, the researcher is often interested not in the morphology but in the rate of heartbeats, which means that it is not the whole signal but only a so-called RR signal, containing the distances of beats, that serves as the basis of spectral processing. This RR signal is inherently discrete and unevenly sampled, which introduces a number of methodological problems: fast Fourier transformation assumes even sampling, and this means that an artificial re-sampling (inserting new samples at equal distances) is necessary. In the case of blood pressure signals, the information is both in the amplitude itself and in the rate, consequently both an RR-like and a full recording-based treatment are usable here. In the present paper we review the different approaches to dealing with unevenly sampled ECG and blood pressure signals, including the Lomb periodogram that does not require re-sampling at all, and argue for a full recording-based treatment of blood pressure fluctuations, as it requires no peak detection and thus avoids all the artefacts that peak detection may cause.

In this paper we have studied how barrier crossing dynamics is affected by colored additive non-Gaussian noise if the barrier fluctuates deterministically. Our investigation indicates that resonant activation(RA) is either enhanced or it becomes robust if noise characteristic is deviated from the Gaussian behavior. We find that additive colored non Gaussian noise can induce the RA-like phenomenon. Another interesting observation is that the turnover behavior persists even in presence of barrier fluctuations at finite rate. Finally, it is observed that mean first passage time(MFPT) decreases with increase of non-Gaussian characteristic of the additive colored noise for a given noise strength and noise correlation time and ultimately reaches to a limiting value. The limiting value remains almost the same if the barrier fluctuating frequency is zero or far from the resonant condition. But near the resonant condition the mean first passage time initially decreases and then increases passing through a minimum as the non Gaussian parameter grows.

We study jamming in granular mixtures from the novel point of view of extended hydrodynamics. Using a hard sphere binary mixture model we predict that a few large grains are expected to get caged more effectively in a matrix of small grains compared to a few small grains in a matrix of larger ones. A similar effect has been experimentally seen in the context of colloidal mixtures.

Fractional oscillator processes of Riemann-Liouville and Weyl type are shown to be locally self-similar. The fractal or Hausdorff dimensions of these processes are determined. Relationship between fractional oscillator processes and the corresponding fractional Brownian motion processes is established.

This review presents the fundamentals of Flicker-Noise Spectroscopy (FNS), a general phenomenological methodology in which the dynamics and structure of complex systems, characterized by non-linear interactions, dissipation, and inertia, are analyzed by extracting information from various signals with stochastically varying components generated by the systems. The basic idea of FNS is to treat the correlation links present in sequences of different irregularities, such as spikes, "jumps", and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study as main information carriers. The tools to extract and analyze the information are power spectra and difference moments (structural functions) of various orders. Presently, FNS can be applied to three types of problems: (1) determination of parameters or patterns that characterize the dynamics or structural features of complex systems; (2) finding precursors of abrupt changes in the state of various complex systems based on a priori information about the dynamics of the systems; and (3) determination of flow dynamics in distributed systems based on the analysis of dynamic correlations in stochastic signals that are simultaneously measured at different points in space. Examples of FNS applications to such problems as parameterization of the images produced with atomic force microscopy (AFM), determination of precursors for electric breakdowns and major earthquakes, and analysis of electric potential fluctuations in electromembrane systems, as well as to some other problems in electrochemistry and medicine are discussed.