Scaling Limits for Gradient Systems in Random Environment

It is well known that the hydrodynamic limit of an interacting particle system satisfying a gradient condition (such as the zero-range process or the symmetric simple exclusion process) is given by a possibly non-linear parabolic equation and the equilibrium fluctuations from this limit are given by a generalized Ornstein-Uhlenbeck process.We prove that in the presence of a symmetric random environment, these scaling limits also hold for almost every choice of the random environment, with an homogenized diffusion coefficient that does not depend on the realization of the random environment.     

Diffusion and mobility in a stirred dense granular material

We describe a probe of diffusivity (D) and mobility (B) for a dense 2D granular system. We introduce random motion by stirring, and characterize D by particle tracking. To measure B we measure the force needed to push a particle through the medium at fixed velocity, v, using three sizes of tracer particle. We find simple Brownian diffusion, but B depends strongly on v because the force needed to push a tracer through a sample is nearly independent of v. Data for D/B depend on the tracer particle size.     

Exact Tracer Diffusion Coefficient in the Asymmetric Random Average Process

We study tracer diffusion in the continuous-time asymmetric random average process which is an interacting particle system on generalizing the Hammersley process. From the equations of motion for the particle-position correlations we obtain the exact tracer diffusion coefficient which is in agreement with a recent heuristic result by Krug and Garcia.     

On the Asymptotic Behavior of an Ornstein-Uhlenbeck Process with Random Forcing

We study the asymptotic behavior of an inertial tracer particle in a random force field. We show that there exists a probability measure, under which the process describing the velocity and environment seen from the vantage point of the moving particle is stationary and ergodic. This measure is equivalent to the underlying probability for the Eulerian flow. As a consequence of the above we obtain the law of large numbers for the trajectory of the tracer. Moreover, we prove also some decorrelation properties of the velocity of the particle, which lead to the existence of a non-degenerate asymptotic covariance tensor. The research of both authors was supported by the Polish Committee for Scientific Research (KBN) grant No. 2PO3A03123.     

Monte Carlo simulation of overdamped motion in a double well potential under the influence of coloured noise

We present a Monte Carlo simulation algorithm for evaluating the stationary probability and the mean and the variance of first passage times in any dynamical system under the influence of additive coloured Gaussian and Marcovian noise (Ornstein-Uhlenbeck process). Our algorithm generates the Ornstein-Uhlenbeck process by a superposition of a finite number of random telegraph processes. We obtain our results from a direct evaluation of the trajectories. We apply our method to the overdamped motion of a particle in a double well potential. We compare our simulation results with various analytic approximations for the stationary probability and the mean first passage times.     

Velocity spectrum for non-Markovian Brownian motion in a periodic potential

Non-Markovian Brownian motion in a periodic potential is studied by means of an electronic analogue simulator. Velocity spectra, the Fourier transforms of velocity autocorrelation functions, are obtained for three types of random force, that is, a white noise, an Ornstein—Uhlenbeck process, and a quasimonochromatic noise. The analogue results are in good agreement both with theoretical ones calculated with the use of a matrix-continued-fraction method, and with the results of digital simulations. An unexpected extra peak in the velocity spectrum is observed for Ornstein-Uhlenbeck noise with large correlation time. The peak is attributed to a slow oscillatory motion of the Brownian particle as it moves back and forth over several lattice spaces. Its relationship to an approximate Langevin equation is discussed.     

Fractional Ornstein-Uhlenbeck processes. Joseph effect in models with infinite variance

We consider five fractional generalizations of the Markovian α-stable Ornstein-Uhlenbeck process and explore the dependence structure of these stochastic models. Since the variance of α-stable distributed random variables is infinite, we describe the dependence structure of the introduced processes in the language of the function called codifference. We present exact formulas for the asymptotic behavior of codifference and answer the question of long-range dependence property (Joseph effect) for the discussed fractional α-stable models. We show that the fractional Ornstein-Uhlenbeck processes can display both Noah and Joseph effect.     

A mechanical model of Brownian motion

We consider a dynamical system consisting of one large massive particle and an infinite number of light point particles. We prove that the motion of the massive particle is, in a suitable limit, described by the Ornstein-Uhlenbeck process. This extends to three dimensions previous results by Holley in one dimension.On leave of the Institut für Theoretische Physik I der Universität Münster. Supported by a Nato fellowshipSupported by NSF Grant, No. PHY 78-03816Supported by NSF Grant, Phy 78-15920     

Stationarity of Lagrangian Velocity¶in Compressible Environments

We study the transport of a passive tracer particle by a random d-dimensional, Gaussian, compressible velocity field. It is well known, since the work of Lumley, see [13], and Port and Stone, see [20], that the observations of the velocity field from the moving particle, the so-called Lagrangian velocity process, are statistically stationary when the field itself is incompressible. In this paper we study the question of stationarity of Lagrangian observations in compressible environments. We show that, given sufficient temporal decorrelation of the velocity statistics, there exists a transformation of the original probability measure, under which the Lagrangian velocity process is time stationary. The transformed probability is equivalent to the original measure. As an application of this result we prove the law of large numbers for the particle trajectory. Received: 1 May 2001 / Accepted: 4 December 2001     

A random walk representation of the Dirac propagator

We define a discrete random walk with a matrix-valued transition function and show that the scaling limit of the two-point function of the walk is given by the Dirac propagator. We study the scaling limit of similar walks with curvature-dependent transition functions, which are analogous to the Ornstein-Uhlenbeck process, and show that the Dirac propagator can be recovered by a limiting procedure.     

Application of integral transforms to a description of the Brownian motion by a non-Markovian random process

The one-dimensional Brownian motion and the Brownian motion of a spherical particle in an infinite medium are described by the conventional methods and integral transforms considering the entrainment of surrounding particles of the medium by the Brownian particle. It is demonstrated that fluctuations of the Brownian particle velocity represent a non-Markovian random process. A harmonic oscillator in a viscous medium is also considered within the framework of the examined model. It is demonstrated that for rheological models, random dynamic processes are also non-Markovian in character. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 2, pp. 66–74, February, 2009.     

Relative distance between tracers as a measure of diffusivity within moving aggregates

Tracking of particles, be it a passive tracer or an actively moving bacterium in the growing bacterial colony, is a powerful technique to probe the physical properties of the environment of the particles. One of the most common measures of particle motion driven by fluctuations and random forces is its diffusivity, which is routinely obtained by measuring the mean squared displacement of the particles. However, often the tracer particles may be moving in a domain or an aggregate which itself experiences some regular or random motion and thus masks the diffusivity of tracers. Here we provide a method for assessing the diffusivity of tracer particles within mobile aggregates by measuring the so-called mean squared relative distance (MSRD) between two tracers. We provide analytical expressions for both the ensemble and time averaged MSRD allowing for direct identification of diffusivities from experimental data.     

Spherical Ornstein-Uhlenbeck Processes

The paper considers random motion of a point on the surface of a sphere, in the case where the angular velocity is determined by an Ornstein-Uhlenbeck process. The solution is fully characterised by only one dimensionless number, the persistence angle, which is the typical angle of rotation during the correlation time of the angular velocity.     

Driven Tracer Particle in One Dimensional Symmetric Simple Exclusion

Consider an infinite system of particles evolving in a one dimensional lattice according to symmetric random walks with hard core interaction. We investigate the behavior of a tagged particle under the action of an external constant driving force. We prove that the diffusively rescaled position of the test particle εX(ε^-2 t), t > 0, converges in probability, as ε→ 0, to a deterministic function v(t). The function v(⋅) depends on the initial distribution of the random environment through a non-linear parabolic equation. This law of large numbers for the position of the tracer particle is deduced from the hydrodynamical limit of an inhomogeneous one dimensional symmetric zero range process with an asymmetry at the origin. An Einstein relation is satisfied asymptotically when the external force is small. Received: 5 December 1996 / Accepted: 30 June 1997     

Spherical particle Brownian motion in viscous medium as non-Markovian random process

The Brownian motion of a spherical particle in an infinite medium is described by the conventional methods and integral transforms considering the entrainment of surrounding particles of the medium by the Brownian particle. It is demonstrated that fluctuations of the Brownian particle velocity represent a non-Markovian random process. The features of Brownian motion in short time intervals and in small displacements are considered.     

Formation of resonance lines in media with stochastic depth dependence of the Planck function

We consider a plane-parallel medium with a stochastic depth dependence of the Planck function, represented by a discrete analog of the Ornstein-Uhlenbeck process. We solve the transfer equation for a two-level atom by means of a matrix-exponential method. Stochastic properties of this process are derived and mean values, variances and probability densities of the specific intensities are evaluated as functions of the angle, frequency and optical depth. For some parameter sets, the situation is simulated numerically and intensity distributions are computed for strong resonance lines.     

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.     

Brownian motion of a charged particle in a magnetic field

We develop and numerically illustrate an exact solution of the multivariate, stochastic, differential equations that govern the velocity and position of a charged particle in a plane normal to a uniform, stationary, magnetic field. The equations self-consistently incorporate the Lorentz force into an Ornstein-Uhlenbeck collision model. Properties of the solution in the infinite dissipation limit are explored and the spectral energy density function is found     

Staggered ladder spectra

We exactly solve a Fokker-Planck equation by determining its eigenvalues and eigenfunctions: we construct nonlinear second-order differential operators which act as raising and lowering operators, generating ladder spectra for the odd- and even-parity states. The ladders are staggered: the odd-even separation differs from even-odd. The Fokker-Planck equation corresponds, in the limit of weak damping, to a generalized Ornstein-Uhlenbeck process where the random force depends upon position as well as time. The process describes damped stochastic acceleration, and exhibits anomalous diffusion at short times and a stationary non-Maxwellian momentum distribution.     

On the Existence of Invariant Measure for Lagrangian Velocity in Compressible Environments

We study transport of a passive tracer particle in a time dependent turbulent flow in the medium with positive molecular diffusivity. We show that there exists then a probability measure equivalent to the underlying physical probability, corresponding to the Eulerian velocity field, under which the particle Lagrangian velocity observations are stationary. As an application we derive the existence of the Stokes drift and the effective diffusivity—the characteristics of the long time behavior of the particle motion.