On stochastic complex beam-beam interaction models with Gaussian colored noise

This paper is to continue our study on complex beam-beam interaction models in particle accelerators with random excitations Y. Xu, W. Xu, G.M. Mahmoud, On a complex beam-beam interaction model with random forcing [Physica A 336 (2004) 347-360]. The random noise is taken as the form of exponentially correlated Gaussian colored noise, and the transition probability density function is obtained in terms of a perturbation expansion of the parameter. Then the method of stochastic averaging based on perturbation technique is used to derive a Fokker-Planck equation for the transition probability density function. The solvability condition and the general transforms using the method of characteristics are proposed to obtain the approximate expressions of probability density function to order ε.Also the exact stationary probability density and the first and second moments of the amplitude are obtained, and one can find when the correlation time equals to zero, the result is identical to that derived from the Stratonovich-Khasminskii theorem for the same model under a broad-band excitation in our previous work.     

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2-Smad4 complex indicates the abnormal enhancement in the transient signal activation process.     

The study on a stochastic system with non-Gaussian noise and Gaussian colored noise

In this paper, a stochastic system with correlation between non-Gaussian noise and Gaussian colored noise is investigated. We carry out the functional methods to derive the approximate Fokker-Planck equation, and the expressions of stationary probability density function and mean first-passage time are presented. Also we explore the effects of correlation between non-Gaussian and Gaussian noise for the mean first-passage time.     

Interface motion in models with stochastic dynamics

We derive the phenomenological dynamics of interfaces from stochastic microscopic models. The main emphasis is on models with a nonconserved order parameter. A slowly varying interface has then a local normal velocity proportional to the local mean curvature. We study bulk models and effective interface models and obtain Green-Kubo-like expressions for the mobility. Also discussed are interface motion in the case of a conserved order parameter, pure surface diffusion, and interface fluctuations. For the two-dimensional Ising model at zero temperature, motion by mean curvature is established rigorously.     

Role of noise in a market model with stochastic volatility

We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the statistical properties of the escape time with reference to the noise enhanced stability (NES) phenomenon, that is the noise induced enhancement of the lifetime of a metastable state. We observe NES effect in our model with stochastic volatility. We investigate the role of the correlation between the two noise sources on the NES effect.     

Evidence of parameter-induced aperiodic stochastic resonance with fixed noise

Stochastic resonance (SR) is based on the cooperative effect between the stochastic dynamical system and the external forcing. As is well known, the cooperative effect is produced by adding noises. In this paper, we show the evidence that by changing the system parameters and the signal intensity, a nonlinear system in the presence of an input aperiodic signal can yield the cooperative effect, with the noise fixed. To quantify the nonlinear system output, we determine the theoretical bit error rate (BER). By numerical simulation, the validity of the theoretical derivation is checked. Besides, we show that parameter-induced SR is more realizable than SR via adding noises, especially when the noise intensity exceeds the resonance level, or when the characteristic of the noise is not known.     

Suprathreshold stochastic firing dynamics with memory in P-type electroreceptors

Weakly electric fish generate a periodic electric field as a carrier signal for active location and communication tasks. Highly sensitive P-type receptors on their surface fire in response to carrier amplitude modulations (AM's) in a noisy phase locked fashion. A simple generic model of receptor activity and signal encoding is presented. Its suprathreshold dynamics, memory and receptor noise reproduce observed firing interval distributions and correlations. The model ultimately explains how smooth responses to AM's are compatible with its nonlinear phase locking properties, and reveals how receptor noise can sometimes enhance the encoding of small yet suprathreshold AM's.     

Nonmarkovian dynamics of stochastic differential equations with quadratic noise

We consider a stochastic differential equation with a quadratic nonlinearity in the noise. We derive equations for the steady state probability density and joint probability distribution valid beyond a markovian approximation. We do not assume that the strength of the random term is small. The equations are derived for the case of an Ornstein-Uhlenbeck noise and also for a dichotomic noise. A comparison is made. We discuss some examples for which correlation functions and the associated relaxation times are calculated.     

Intrinsic resistive switching and memory effects in silicon oxide

Resistive switching behaviors are described in silicon oxide (SiO _x ) systems employing vertical E/SiO _x /E (E denotes the electrode) structures. The switching is largely independent of the electrode material and attributed to the intrinsic properties of SiO _x . Based on the recent experimental observation (Yao et al. in Nano Lett. 10:4105, 2010) of a silicon filament embedded in the SiO _x matrix, we further discuss the switching mechanism in light of the measured electrical phenomena. The set voltages are largely SiO _x -thickness independent, consistent with the mechanistic picture of point switching in the silicon filament. The multi-state switching and shifts in the set voltages with respect to the reset voltages are consistent with an electrochemical redox process (Si ↔ SiO _y ) at the switching site.     

Intrinsic noise of semiconductor lasers in optical communication systems

The upper limit of the achievable signal-to-noise ratio in optical communication systems is determined by the intrinsic laser noise due to quantum fluctuations inside the laser cavity. This achievable signal-to-noise ratio depends on the way in which different lasing modes are detected; wavelength filtering and material dispersion may yield a significant deterioration of the signal-to-noise ratio. It is concluded from theoretical calculations and from measurements on V-groove lasers that a d.c. signal-to-noise ratio of about 70 dB may be achieved for a noise bandwidth of 10 MHz.     

The nature of bursting noises,stochastic resonance and deterministic chaos in excitable neurons

We study the Hindmarsh-Rose model of excitable neurons and show that in the asymptotic limit this monostable model can possess some kind of dynamical bistability: small-amplitude quasiharmonic and large-amplitude relaxational oscillations can be simultaneously excited and their formation is accompanied by a narrow hysteresis. We show that bursting noises, stochastic resonance and deterministic chaos are determined by random transitions between these two dynamical states under slow and small changes of one of the model variables (z). We find that these effects take place even for such model parameters when hysteresis transforms into a step and they disappear when this step is smoothed out enough. We analyze some characteristics and conditions of formation of the deterministic chaos. We emphasize that such dynamical bistability and the effects related to it are universal phenomena and occur in a wide class of dynamical systems of different nature including brusselator.     

Generic transient memory formation in disordered systems with noise

Out-of-equilibrium disordered systems may form memories of external driving in a remarkable fashion. The system "remembers" multiple values from a series of training inputs yet "forgets" nearly all of them at long times despite the inputs being continually repeated. Here, learning and forgetting are inseparable aspects of a single process. The memory loss may be prevented by the addition of noise. We identify a class of systems with this behavior, giving as an example a model of non-Brownian suspensions under cyclic shear.