Multifractal characterization of stochastic resonance

We use a multifractal formalism to study the effect of stochastic resonance in a noisy bistable system driven by various input signals. To characterize the response of a stochastic bistable system we introduce a new measure based on the calculation of a singularity spectrum for a return time sequence. We use wavelet transform modulus maxima method for the singularity spectrum computations. It is shown that the degree of multifractality defined as a width of singularity spectrum can be successfully used as a measure of complexity both in the case of periodic and aperiodic (stochastic or chaotic) input signals. We show that in the case of periodic driving force singularity spectrum can change its structure qualitatively becoming monofractal in the regime of stochastic synchronization. This fact allows us to consider the degree of multifractality as a new measure of stochastic synchronization also. Moreover, our calculations have shown that the effect of stochastic resonance can be catched by this measure even from a very short return time sequence. We use also the proposed approach to characterize the noise-enhanced dynamics of a coupled stochastic neurons model.Comment: 10 pages, 21 EPS-figures, RevTe

On the driven Frenkel-Kontorova model: II. Chaotic sliding and nonequilibrium melting and freezing

The dynamical behavior of a weakly damped harmonic chain in a spatially periodic potential (Frenkel-Kontorova model) under the subject of an external force is investigated. We show that the chain can be in a spatio-temporally chaotic state called fluid-sliding state. This is proven by calculating correlation functions and Lyapunov spectra. An effective temperature is attributed to the fluid-sliding state. Even though the velocity fluctuations are Gaussian distributed, the fluid-sliding state is clearly not in equilibrium because the equipartition theorem is violated. We also study the transition between frozen states (stationary solutions) and=7F molten states (fluid-sliding states). The transition is similar to a first-order phase transition, and it shows hysteresis. The depinning-pinning transition (freezing) is a nucleation process. The frozen state contains usually two domains of different particle densities. The pinning-depinning transition (melting) is caused by saddle-node bifurcations of the stationary states. It depends on the history. Melting is accompanied by precursors, called micro-slips, which reconfigurate the chain locally. Even though we investigate the dynamics at zero temperature, the behavior of the Frenkel-Kontorova model is qualitatively similar to the behavior of similar models at nonzero temperature.Comment: Written in RevTeX, 13 figures in PostScript, appears in PR

Fluctuation Relation beyond Linear Response Theory

The Fluctuation Relation (FR) is an asymptotic result on the distribution of certain observables averaged over time intervals T as T goes to infinity and it is a generalization of the fluctuation--dissipation theorem to far from equilibrium systems in a steady state which reduces to the usual Green-Kubo (GK) relation in the limit of small external non conservative forces. FR is a theorem for smooth uniformly hyperbolic systems, and it is assumed to be true in all dissipative ``chaotic enough'' systems in a steady state. In this paper we develop a theory of finite time corrections to FR, needed to compare the asymptotic prediction of FR with numerical observations, which necessarily involve fluctuations of observables averaged over finite time intervals T. We perform a numerical test of FR in two cases in which non Gaussian fluctuations are observable while GK does not apply and we get a non trivial verification of FR that is independent of and different from linear response theory. Our results are compatible with the theory of finite time corrections to FR, while FR would be observably violated, well within the precision of our experiments, if such corrections were neglected.Comment: Version accepted for publication on the Journal of Statistical Physics; minor changes; two references adde

Bistability and chaos at low-level of quanta

We study nonlinear phenomena of bistability and chaos at a level of few quanta. For this purpose we consider a single-mode dissipative oscillator with strong Kerr nonlinearity with respect to dissipation rate driven by a monochromatic force as well as by a train of Gaussian pulses. The quantum effects and decoherence in oscillatory mode are investigated on the framework of the purity of states and the Wigner functions calculated from the master equation. We demonstrate the quantum chaotic regime by means of a comparison between the contour plots of the Wigner functions and the strange attractors on the classical Poincar\'e section. Considering bistability at low-limit of quanta, we analyze what is the minimal level of excitation numbers at which the bistable regime of the system is displayed? We also discuss the formation of oscillatory chaotic regime by varying oscillatory excitation numbers at ranges of few quanta. We demonstrate quantum-interference phenomena that are assisted hysteresis-cycle behavior and quantum chaos for the oscillator driven by the train of Gaussian pulses as well as we establish the border of classical-quantum correspondence for chaotic regimes in the case of strong nonlinearities.Comment: 10 pages, 14 figure

Spontaneous and stimulus-induced coherent states of critically balanced neuronal networks

How the information microscopically processed by individual neurons is integrated and used in organizing the behavior of an animal is a central question in neuroscience. The coherence of neuronal dynamics over different scales has been suggested as a clue to the mechanisms underlying this integration. Balanced excitation and inhibition may amplify microscopic fluctuations to a macroscopic level, thus providing a mechanism for generating coherent multiscale dynamics. Previous theories of brain dynamics, however, were restricted to cases in which inhibition dominated excitation and suppressed fluctuations in the macroscopic population activity. In the present study, we investigate the dynamics of neuronal networks at a critical point between excitation-dominant and inhibition-dominant states. In these networks, the microscopic fluctuations are amplified by the strong excitation and inhibition to drive the macroscopic dynamics, while the macroscopic dynamics determine the statistics of the microscopic fluctuations. Developing a novel type of mean-field theory applicable to this class of interscale interactions, we show that the amplification mechanism generates spontaneous, irregular macroscopic rhythms similar to those observed in the brain. Through the same mechanism, microscopic inputs to a small number of neurons effectively entrain the dynamics of the whole network. These network dynamics undergo a probabilistic transition to a coherent state, as the magnitude of either the balanced excitation and inhibition or the external inputs is increased. Our mean-field theory successfully predicts the behavior of this model. Furthermore, we numerically demonstrate that the coherent dynamics can be used for state-dependent read-out of information from the network. These results show a novel form of neuronal information processing that connects neuronal dynamics on different scales.Comment: 20 pages 12 figures (main text) + 23 pages 6 figures (Appendix); Some of the results have been removed in the revision in order to reduce the volume. See the previous version for more result

Disorder Induced Diffusive Transport In Ratchets

The effects of quenched disorder on the overdamped motion of a driven particle on a periodic, asymmetric potential is studied. While for the unperturbed potential the transport is due to a regular drift, the quenched disorder induces a significant additional chaotic ``diffusive'' motion. The spatio-temporal evolution of the statistical ensemble is well described by a Gaussian distribution, implying a chaotic transport in the presence of quenched disorder.Comment: 10 pages, 4 EPS figures; submitted to Phys. Rev. Letter

Is it possible to experimentally verify the fluctuation relation? A review of theoretical motivations and numerical evidence

The theoretical motivations to perform experimental tests of the stationary state fluctuation relation are reviewed. The difficulties involved in such tests, evidenced by numerical simulations, are also discussed.Comment: 36 pages, 4 figures. Extended version of a presentation to the discussion "Is it possible to experimentally verify the fluctuation theorem?", IHP, Paris, December 1, 2006. Comments are very welcom