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At least 775 records · Page 43Linked to original sources

Phase diffusion as a model for coherent suppression of tunneling in the presence of noise.

We study the stabilization of coherent suppression of tunneling in a driven double-well system subject to random periodic delta-function "kicks." We model dissipation due to this stochastic process as a phase diffusion process for an effective two-level system, and derive a corresponding set of Bloch equations with phase damping terms that agree with the periodically kicked system at discrete times. We demonstrate that the ability of noise to localize the system on either side of the double-well potential arises from overdamping of the phase of oscillation, and not from any cooperative effect between the noise and the driving field. The model is investigated with a square wave drive, which has qualitatively similar features to the widely studied cosinusoidal drive, but has the additional advantage of allowing one to derive exact analytic expressions.

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Brownian motion in a magnetic field.

We derive explicit forms of Markovian transition probability densities for the velocity-space, phase-space, and the Smoluchowski configuration-space Brownian motion of a charged particle in a constant magnetic field. By invoking a hydrodynamical formalism for those stochastic processes, we quantify a continual (net on the local average) heat transfer from the thermostat to diffusing particles.

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Strong desynchronizing effects of weak noise in globally coupled systems.

In assemblies of globally coupled dynamical units, weak noise perturbing independently the individual units can cause anomalous dispersion in the synchronized cloud of the units in the phase space. When the noise-free dynamics of the synchronized assembly is nonperiodic, various moments of the linear dimension of the cloud as a function of the noise strength exhibit multiscaling properties with parameter-dependent scaling exponents. Some numerical evidence of this peculiar behavior as well as its interpretation in terms of a multiplicative stochastic process with small additive noise is provided. Universality of the phenomenon is also discussed.

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Kinetic Ashkin-Teller model with competing dynamics.

We study a two-dimensional nonequilibrium Ashkin-Teller model based on competing dynamics induced by contact with a heat bath at temperature T, and subject to an external source of energy. The dynamics of the system is simulated by two competing stochastic processes: a Glauber dynamics with probability p, which simulates the contact with the heat bath; and a Kawasaki dynamics with probability 1-p, which takes into account the flux of energy into the system. Monte Carlo simulations were employed to determine the phase diagram for the stationary states of the model and the corresponding critical exponents. The phase diagrams of the model exhibit a self-organization phenomenon for certain values of the fourth coupling interaction strength. On the other hand, from exponent calculations, the equilibrium critical behavior is preserved when nonequilibrium conditions are applied.

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Refined scaling hypothesis for breakdown coefficients in turbulence.

We study the statistics of Novikov's breakdown coefficients, which represent ratios between energy dissipation rates at different length scales in turbulence. The distribution of their logarithms is shown to be very closely reproduced by an analytic function that we obtain from a hierarchical stochastic process for the turbulent cascade. Correlations and deviation from Gaussianity in the model are accounted for by two parameters, one of which can be interpreted as a generalized dimension. Finally, we illustrate the lack of power-law scaling in the moments of the breakdown coefficients and propose an analytical approximation scheme for them.

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Possible physical meaning of the Tsallis entropy parameter.

Since the proposal of the Tsallis generalized entropy, the general explanation of the role played by the parameter q that defines which specific entropy to pick among a whole family, remained somewhat partial and tentative, although some particular examples were taken into account specifically. The purpose of the present paper is to present a rigorous formal derivation of a mathematical expression giving the parameter q in terms of the momentum fluctuations of a stochastic process, thus furnishing at least one of its possible physical origins.

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Persistence in a stationary time series.

We study the persistence in a class of continuous stochastic processes that are stationary only under integer shifts of time. We show that under certain conditions, the persistence of such a continuous process reduces to the persistence of a corresponding discrete sequence obtained from the measurement of the process only at integer times. We then construct a specific sequence for which the persistence can be computed even though the sequence is non-Markovian. We show that this may be considered as a limiting case of persistence in the diffusion process on a hierarchical lattice.

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Surrogate for nonlinear time series analysis.

We present a surrogate for use in nonlinear time series analysis. This surrogate algorithm has significant advantages over the most commonly used surrogates, in that it provides a more robust statistical test by producing an entire population of surrogates that are consistent with the null hypothesis. We will show that for the currently used surrogate algorithms, although individual surrogate files are consistent with the null hypothesis the population of surrogates generated is not. The surrogate is tested on a linear stochastic process and a continuous nonlinear system.

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Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state.

We compare dynamical properties of brain electrical activity from different recording regions and from different physiological and pathological brain states. Using the nonlinear prediction error and an estimate of an effective correlation dimension in combination with the method of iterative amplitude adjusted surrogate data, we analyze sets of electroencephalographic (EEG) time series: surface EEG recordings from healthy volunteers with eyes closed and eyes open, and intracranial EEG recordings from epilepsy patients during the seizure free interval from within and from outside the seizure generating area as well as intracranial EEG recordings of epileptic seizures. As a preanalysis step an inclusion criterion of weak stationarity was applied. Surface EEG recordings with eyes open were compatible with the surrogates' null hypothesis of a Gaussian linear stochastic process. Strongest indications of nonlinear deterministic dynamics were found for seizure activity. Results of the other sets were found to be inbetween these two extremes.

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Generalized theory and simulation of spontaneous and super-radiant emissions in electron devices and free-electron lasers.

A unified formulation of spontaneous (shot-noise) and super-radiant emissions in electron devices is presented. We consider an electron beam with an arbitrary temporal current modulation propagating through the interaction region of the electronic device. The total electromagnetic field is presented as a stochastic process and expanded in terms of transverse eigenmodes of the medium (free space or waveguide), in which the field is excited and propagates. Using the waveguide excitation equations, formulated in the frequency domain, an analytical expression for the power spectral density of the electromagnetic radiation is derived. The spectrum of the excited radiation is shown to be composed of two terms, which are the spontaneous and super-radiant emissions. For a continuous, unmodulated beam, the shot noise produces only incoherent spontaneous emission of a power proportional to the flux eI(0) (DC current) of the particles in the electron beam. When the beam is modulated or prebunched, a partially coherent super-radiant emission is also produced with power proportional to the current spectrum /I(omega)/(2). Based on a three-dimensional model, a numerical particle simulation code was developed. A set of coupled-mode excitation equations in the frequency domain are solved self-consistently with the equations of particles motion. The simulation considers random distributions of density and energy in the electron beam and takes into account the statistical and spectral features of the excited radiation. At present, the code can simulate free-electron lasers (FELs) operation in various modes: spontaneous and self-amplified spontaneous emission, super-radiance and stimulated emission, in the linear and nonlinear Compton or Raman regimes. We employed the code to demonstrate spontaneous and super-radiant emission excited when a prebunched electron beam passes through a wiggler of an FEL.

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Velocity correlations, diffusion, and stochasticity in a one-dimensional system.

We consider the motion of a test particle in a one-dimensional system of equal-mass point particles. The test particle plays the role of a microscopic "piston" that separates two hard-point gases with different concentrations and arbitrary initial velocity distributions. In the homogeneous case when the gases on either side of the piston are in the same macroscopic state, we compute and analyze the stationary velocity autocorrelation function C(t). Explicit expressions are obtained for certain typical velocity distributions, serving to elucidate in particular the asymptotic behavior of C(t). It is shown that the occurrence of a nonvanishing probability mass at zero velocity is necessary for the occurrence of a long-time tail in C(t). The conditions under which this is a t(-3) tail are determined. Turning to the inhomogeneous system with different macroscopic states on either side of the piston, we determine its effective diffusion coefficient from the asymptotic behavior of the variance of its position, as well as the leading behavior of the other moments about the mean. Finally, we present an interpretation of the effective noise arising from the dynamics of the two gases, and thence that of the stochastic process to which the position of any particle in the system reduces in the thermodynamic limit.

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Nonequilibrium antiferromagnetic mixed-spin Ising model.

We studied an antiferromagnetic mixed-spin Ising model on the square lattice subject to two competing stochastic processes. The model system consists of two interpenetrating sublattices of spins sigma=1/2 and S=1, and we take only nearest neighbor interactions between pairs of spins. The system is in contact with a heat bath at temperature T, and the exchange of energy with the heat bath occurs via one-spin flip (Glauber dynamics). Besides, the system interacts with an external agency of energy, which supplies energy to it whenever two nearest neighboring spins are simultaneously flipped. By employing Monte Carlo simulations and a dynamical pair approximation, we found the phase diagram for the stationary states of the model in the plane temperature T versus the competition parameter between one- and two-spin flips p. We observed the appearance of three distinct phases, that are separated by continuous transition lines. We also determined the static critical exponents along these lines and we showed that this nonequilibrium model belongs to the universality class of the two-dimensional equilibrium Ising model.

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Ballistic flights and random diffusion as building blocks for Hamiltonian kinetics.

We propose a kinetic approach to transport in Hamiltonian systems with a mixed phase space. The approach is based on the decomposition of the dynamical picture into two contributions: (a) ballistic flights, and (b) random diffusion. The kinetic scheme leads to a stochastic process with statistical properties which are similar to those produced by the original Hamiltonian. We show that our approach helps in obtaining an insight into several properties of Hamiltonian kinetics such as anomalous diffusion, chaos-assisted population exchange, and current rectification. In particular, the chaos-assisted exchange offers a classical counterpart for the recently reported chaos-assisted tunneling.

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Diffusion of epicenters of earthquake aftershocks, Omori's law, and generalized continuous-time random walk models.

The epidemic-type aftershock sequence (ETAS) model is a simple stochastic process modeling seismicity, based on the two best-established empirical laws, the Omori law (power-law decay approximately 1/t(1+theta) of seismicity after an earthquake) and Gutenberg-Richter law (power-law distribution of earthquake energies). In order to describe also the space distribution of seismicity, we use in addition a power-law distribution approximately 1/r(1+mu) of distances between triggered and triggering earthquakes. The ETAS model has been studied for the last two decades to model real seismicity catalogs and to obtain short-term probabilistic forecasts. Here, we present a mapping between the ETAS model and a class of CTRW (continuous time random walk) models, based on the identification of their corresponding master equations. This mapping allows us to use the wealth of results previously obtained on anomalous diffusion of CTRW. After translating into the relevant variable for the ETAS model, we provide a classification of the different regimes of diffusion of seismic activity triggered by a mainshock. Specifically, we derive the relation between the average distance between aftershocks and the mainshock as a function of the time from the mainshock and of the joint probability distribution of the times and locations of the aftershocks. The different regimes are fully characterized by the two exponents theta and mu. Our predictions are checked by careful numerical simulations. We stress the distinction between the "bare" Omori law describing the seismic rate activated directly by a mainshock and the "renormalized" Omori law taking into account all possible cascades from mainshocks to aftershocks of aftershock of aftershock, and so on. In particular, we predict that seismic diffusion or subdiffusion occurs and should be observable only when the observed Omori exponent is less than 1, because this signals the operation of the renormalization of the bare Omori law, also at the origin of seismic diffusion in the ETAS model. We present predictions and insights provided by the ETAS to CTRW mapping which suggest different ways for studying seismic catalogs. Finally, we discuss the present evidence for our predicted subdiffusion of seismicity triggered by a main shock, stressing the caveats and limitations of previous empirical works.

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From gene families and genera to incomes and internet file sizes: why power laws are so common in nature.

We present a simple explanation for the occurrence of power-law tails in statistical distributions by showing that if stochastic processes with exponential growth in expectation are killed (or observed) randomly, the distribution of the killed or observed state exhibits power-law behavior in one or both tails. This simple mechanism can explain power-law tails in the distributions of the sizes of incomes, cities, internet files, biological taxa, and in gene family and protein family frequencies.

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Models for correlated multifractal hypersurfaces.

We discuss and implement computer approximations of fractal and multifractal hypersurfaces. These hypersurfaces consist of reconstructions of a stochastic process in the real space from randomly distributed variables in the discrete wavelet domain. The synthetic surfaces have the usual fractional Brownian motion as a particular case, and inherit the correlation structure of these fractals. We first introduce the one-dimensional version of these surfaces that obey a weak self-affine symmetry. This symmetry appears in the wavelet domain as a condition on the second moments of the probability distributions of the wavelet coefficients. Then we use these relations to define the fractals and multifractals in d dimensions. Finally, we concentrate on the generation of samples of these hypersurfaces.

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Epidemic spreading with immunization and mutations.

The spreading of infectious diseases with and without immunization of individuals can be modeled by stochastic processes that exhibit a transition between an active phase of epidemic spreading and an absorbing phase, where the disease dies out. In nature, however, the transmitted pathogen may also mutate, weakening the effect of immunization. In order to study the influence of mutations, we introduce a model that mimics epidemic spreading with immunization and mutations. The model exhibits a line of continuous phase transitions and includes the general epidemic process (GEP) and directed percolation (DP) as special cases. Restricting to perfect immunization in two spatial dimensions, we analyze the phase diagram and study the scaling behavior along the phase transition line as well as in the vicinity of the GEP point. We show that mutations lead generically to a crossover from the GEP to DP. Using standard scaling arguments, we also predict the form of the phase transition line close to the GEP point. The protection gained by immunization is vitally decreased by the occurrence of mutations.

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Symbolic stochastic dynamical systems viewed as binary N-step Markov chains.

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In the model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities among the preceding N symbols. The correlation and distribution functions as well as the variance of the number of symbols in the words of arbitrary length L are obtained analytically and numerically. A self-similarity of the studied stochastic process is revealed and the similarity group transformation of the chain parameters is presented. The diffusion Fokker-Planck equation governing the distribution function of the L words is explored. If the persistent correlations are not extremely strong, the distribution function is shown to be the Gaussian with the variance being nonlinearly dependent on L. The applicability of the developed theory to the coarse-grained written and DNA texts is discussed.

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