Probability Of Large Fluctuations Research Articles

Gap probability and full counting statistics in the one-dimensional one-component plasma

We consider the 1d one-component plasma in thermal equilibrium, consisting of N equally charged particles on a line, with pairwise Coulomb repulsion and confined by an external harmonic potential. We study two observables: (i) the distribution of the gap between two consecutive particles in the bulk and (ii) the distribution of the number of particles N I in a fixed interval I = [−L, +L] inside the bulk, the so-called full-counting-statistics (FCS). For both observables, we compute, for large N, the distribution of the typical as well as atypical large fluctuations. We show that the distribution of the typical fluctuations of the gap g is described by the scaling form , where α is the interaction coupling and the scaling function H α (z) is computed explicitly. It has a faster than Gaussian tail for large z: as z → ∞. Similarly, for the FCS, we show that the distribution of the typical fluctuations of N I is described by the scaling form , where is the average value of N I and the scaling function U α (z) is obtained explicitly. For both observables, we show that the probability of large fluctuations is described by large deviations forms with respective rate functions that we compute explicitly. Our numerical Monte-Carlo simulations are in good agreement with our analytical predictions.

Enhancement of large fluctuations to extinction in adaptive networks.

During an epidemic, individual nodes in a network may adapt their connections to reduce the chance of infection. A common form of adaption is avoidance rewiring, where a noninfected node breaks a connection to an infected neighbor and forms a new connection to another noninfected node. Here we explore the effects of such adaptivity on stochastic fluctuations in the susceptible-infected-susceptible model, focusing on the largest fluctuations that result in extinction of infection. Using techniques from large-deviation theory, combined with a measurement of heterogeneity in the susceptible degree distribution at the endemic state, we are able to predict and analyze large fluctuations and extinction in adaptive networks. We find that in the limit of small rewiring there is a sharp exponential reduction in mean extinction times compared to the case of zero adaption. Furthermore, we find an exponential enhancement in the probability of large fluctuations with increased rewiring rate, even when holding the average number of infected nodes constant.

Money-based Inflation Risk Indicator:a regime Switching Model

We examine the relationship between probability of large fluctuations of inflation rate and monetary developments. With this purpose we identify the periods of high inflation regime for the cross-section of 15 transition economies. The obtained results are used to estimate the panel probit models that capture the relationship between probability of transition to a high inflation regime and money growth. We calculate the conditional probability of transition to a high inflation regime that may be regarded as a money-based inflation risk indicator for Russia.

Statistics of Fourier modes in a turbulent flow.

Fourier series are often used to discuss the properties of a homogeneous turbulent field. We investigate the statistics of Fourier modes of the turbulent velocity field and of a passive scalar. The statistics of individual Fourier modes is known to be Gaussian when the size of the system L is much larger that the integral (correlation) size l(0). The case where the integral size is of the order of the system size L approximately l(0), is studied by direct numerical simulations in the range 20 < or approximately = Rlambda < or approximately = 80. At a given Rlambda, we find that the probabilities of large fluctuations become larger when the wave number increases, in qualitative agreement with the notion of intermittency. As the Reynolds number increases, however, the probability density functions become closer to Gaussian, in sharp contrast with the behavior of velocity increments. We also show that in a simple model of cascade, the Fourier series decomposition is not appropriate to capture intermittency effects. Last, we discuss other issues related to our results.

Statistics of soliton-bearing systems with additive noise.

We present a consistent method to calculate the probability distribution of soliton parameters in systems with additive noise. Even though the noise is weak, we are interested in probabilities of large fluctuations (generally non-Gaussian) which are beyond perturbation theory. Our method is a development of the instanton formalism (method of optimal fluctuation) based on a saddle-point approximation in the path integral. We first solve a fundamental problem of soliton statistics governed by a noisy nonlinear Schrödinger equation. We then apply our method to optical soliton transmission systems using signal control elements (filters and amplitude and phase modulators).

Modeling river flows with heavy tails

Recent advances in time series analysis provide alternative models for river flows in which the innovations have heavy tails, so that some of the moments do not exist. The probability of large fluctuations is much larger than for standard models. We survey some recent theoretical developments for heavy tail time series models and illustrate their practical application to river flow data from the Salt River near Roosevelt, Arizona. We also include some simple diagnostics that the practitioner can use to identify when the methods of this paper may be useful.

Hydrodynamics and fluctuations outside of local equilibrium: Driven diffusive systems

We derive hydrodynamic equations for systems not in local thermodynamic equilibrium, that is, where the local stationary measures are “non-Gibbsian” and do not satisfy detailed balance with respect to the microscopic dynamics. As a main example we consider thedriven diffusive systems (DDS), such as electrical conductors in an applied field with diffusion of charge carriers. In such systems, the hydrodynamic description is provided by a nonlinear drift-diffusion equation, which we derive by a microscopic method ofnonequilibrium distributions. The formal derivation yields a Green-Kubo formula for the bulk diffusion matrix and microscopic prescriptions for the drift velocity and “nonequilibrium entropy” as functions of charge density. Properties of the hydrodynamic equations are established, including an “H-theorem” on increase of the thermodynamic potential, or “entropy”, describing approach to the homogeneous steady state. The results are shown to be consistent with the derivation of the linearized hydrodynamics for DDS by the Kadanoff-Martin correlation-function method and with rigorous results for particular models. We discuss also the internal noise in such systems, which we show to be governed by a generalizedfluctuation-dissipation relation (FDR), whose validity is not restricted to thermal equilibrium or to time-reversible systems. In the case of DDS, the FDR yields a version of a relation proposed some time ago by Price between the covariance matrix of electrical current noise and the bulk diffusion matrix of charge density. Our derivation of the hydrodynamic laws is in a form—the so-called “Onsager force-flux form” which allows us to exploit the FDR to construct the Langevin description of the fluctuations. In particular, we show that the probability of large fluctuations in the hydrodynamic histories is governed by a version of the Onsager “principle of least dissipation,” which estimates the probability of fluctuations in terms of the Ohmic dissipation required to produce them and provides a variational characterization of the most probable behavior as that associated to least (excess) dissipation. Finally, we consider the relation of longrange spatial correlations in the steady state of the DDS and the validity of ordinary hydrodynamic laws. We also discuss briefly the application of the general methods of this paper to other cases, such as reaction-diffusion systems or magnetohydrodynamics of plasmas.