Phase velocity and phase diffusion in periodically driven discrete-state systems

SYNCHRONIZATION AND TRANSPORT IN AN OSCILLATING PERIODIC POTENTIAL

We study the motion of overdamped Brownian particles in a periodic potential with a temporally oscillating amplitude. First we investigate diffusive motion in the untitled potential. Furthermore, if a constant force is applied, the oscillating potential induces a synchronized motion. The deterministic dynamics becomes in resonance with the potential oscillations. This dynamics gives rise to a transport with extremely low dispersion. We distinguish slow and fast oscillatory driving and give analytical expressions for the mean velocity and effective diffusion.

Synchronization of weakly perturbed Markov chain oscillators

Rate processes are simple and analytically tractable models for many dynamical systems that switch stochastically between a discrete set of quasistationary states; however, they may also approximate continuous processes by coarse-grained, symbolic dynamics. In contrast to limit-cycle oscillators that are weakly perturbed by noise, in such systems, stochasticity may be strong, and topologies more complicated than a circle can be considered. Here we apply a second-order time-dependent perturbation theory to derive expressions for the mean frequency and phase diffusion constant of discrete-state oscillators coupled or driven through weakly time-dependent transition rates. We also describe a method of global control to optimize the response of the mean frequency in complex transition networks.

Stochastic hierarchical systems: excitable dynamics

We present a discrete model of stochastic excitability by a low-dimensional set of delayed integral equations governing the probability in the rest state, the excited state, and the refractory state. The process is a random walk with discrete states and nonexponential waiting time distributions, which lead to the incorporation of memory kernels in the integral equations. We extend the equations of a single unit to the system of equations for an ensemble of globally coupled oscillators, derive the mean field equations, and investigate bifurcations of steady states. Conditions of destabilization are found, which imply oscillations of the mean fields in the stochastic ensemble. The relation between the mean field equations and the paradigmatic Kuramoto model is shown.

Role of fluctuations in the response of coupled bistable units to weak time-periodic driving forces

We analyze the stochastic response of a finite set of globally coupled noisy bistable units driven by rather weak time-periodic forces. We focus on the stochastic resonance and phase frequency synchronization of the collective variable, defined as the arithmetic mean of the variable characterizing each element of the array. For single-unit systems, stochastic resonance can be understood with the powerful tools of linear response theory. Proper noise-induced phase frequency synchronization for a single-unit system in this linear response regime does not exist. For coupled arrays, our numerical simulations indicate an enhancement of the stochastic resonance effects leading to gains larger than unity as well as genuine phase frequency synchronization. The nonmonotonicity of the response with the strength of the coupling strength is investigated. Comparison with simplifying schemes proposed in the literature to describe the random response of the collective variable is carried out.

Frequency dependence of phase-synchronization time in nonlinear dynamical systems

It has been found recently that the averaged phase-synchronization time between the input and the output signals of a nonlinear dynamical system can exhibit an extremely high sensitivity to variations in the noise level. In real-world signal-processing applications, sensitivity to frequency variations may be of considerable interest. Here we investigate the dependence of the averaged phase-synchronization time on frequency of the input signal. Our finding is that, for typical nonlinear oscillator systems, there can be a frequency regime where the time exhibits significant sensitivity to frequency variations. We obtain an analytic formula to quantify the frequency dependence, provide numerical support, and present experimental evidence from a simple nonlinear circuit system.

Periodic driving controls random motion of Brownian steppers

We study the motion of Brownian steppers, which are objects moving unidirectionally by discrete steps. A single step is composed of two processes. An activation process describing the random attachment of a fuel molecule is followed by a conformational change of the stepper, leading to the forward motion. Whereas activation is given by a Markovian rate process, the forward motion is defined by a gamma distribution. In this paper we propose a periodic modulation of the fuel concentration in order to control the random motion of the stepper. We show that the driving may reduce the fluctuations of the stepper. Corresponding minima of the diffusion coefficient and maxima of the Péclet number prove the regularity of the motion.