Empirical estimates of the average orders of orbits period lengths in Euler groups

The averaged growth rate of period's length of the geometrical progressions $\text{{q}{}^{\mathrm{t}}\text{mod}\text{n,}\text{t=0,1,…}}$ for increasing n is empirically estimated for different values of q. The experimental results, obtained for n up to 10⁶, allow us to conjecture that the average order of period's length is $\text{C}\text{n}\text{ln}\text{(n)}$, where constant C depends on q. To cite this article: F. Aicardi, C. R. Acad. Sci. Paris, Ser. I 339 (2004).     

Identity-based learning and segregation in social networks under different institutional environments

To study the evolution of segregation in social networks across systems embedded in different institutional environments, we develop an identity-based learning model where segregation is stochastically conditioned by the initial distribution of the actor’s attention to identity and the updating of this distribution over time. The updating process, which we call the process of mutual learning multiplier, is based on an actor’s success and failure experiences in tying with the same-subgroup and cross-subgroup actors. Results from a Monte Carlo simulation of the model show that the mutual learning multiplier produces disproportional relationships between the initial distribution of identity attention and the level of segregation in social networks. We also find that those relationships are affected by the actors’ attention to structural holes, rate of learning from experience, system size, and the identity heterogeneity of the system. Overall, the model provides insights into various dynamics of network structuration across time and space.     

Asymptotic behavior of diffusion problems in a domain made of two cylinders of different diameters and lengths

We study the asymptotic behavior of the solution of a diffusion problem posed in the union of a cylinder of small diameter and fixed length with another cylinder with much smaller diameter and length. The Dirichlet condition is assumed to hold at both extremities of this domain. Depending on the relative size of the parameters, we show that the boundary condition of the one-dimensional limit problem is a Dirichlet, Fourier or Neumann condition. We also prove a corrector result for every case. To cite this article: J. Casado-D??az et al., C. R. Acad. Sci. Paris, Ser. I 338 (2004).     

Averaging in Markov Models with Fast Markov Switches and Applications to Queueing Models

An approximation of Markov type queueing models with fast Markov switches by Markov models with averaged transition rates is studied. First, an averaging principle for two-component Markov process (x _n (t), _n (t)) is proved in the following form: if a component x _n () has fast switches, then under some asymptotic mixing conditions the component _n () weakly converges in Skorokhod space to a Markov process with transition rates averaged by some stationary measures constructed by x _n (). The convergence of a stationary distribution of (x _n (), _n ()) is studied as well. The approximation of state-dependent queueing systems of the type M _M,Q /M _M,Q /m/N with fast Markov switches is considered.     

Gradient estimate for solutions to Poisson equations in metric measure spaces

Let (X,d) be a complete, pathwise connected metric measure space with a locally Ahlfors Q-regular measure μ, where Q>1. Suppose that (X,d,μ) supports a (local) (1,2)-Poincaré inequality and a suitable curvature lower bound. For the Poisson equation Δu=f on (X,d,μ), Moser-Trudinger and Sobolev inequalities are established for the gradient of u. The local Hölder continuity with optimal exponent of solutions is obtained.     

Optimal experimental design to estimate the correlation coefficient in a gaussian model

The article considers the problem of finding the distribution function of the components of a stochastic finite-dimensional vector from nonsimultaneous observations of the vector components. An experimental procedure is proposed in which the observation process is related with some instrumental random variable distributed independently of the experimentally observed vector, and the relationship between the two variables is chosen in an optimal manner. The optimal control distribution minimizes the correlation coefficients of the observed vector components. The minimization problem is solved and an optimal experimental procedure is described. Translated from Algoritmy Upravleniya i Identifikatsii, pp. 17–25, 1997.     

The pointwise estimate of solutions to the parabolic conservation law in multi-dimensions

In this paper we consider the parabolic conservation law with large initial data which has a big perturbation. Using the method of Green function, we first obtain the decay rates of the derivatives of the solutions in L ² and L ^∞ spaces, and then the pointwise estimate of the solutions.     

A universal approach to estimate the conditional variance in semimartingale limit theorems

The typical central limit theorems in high-frequency asymptotics for semimartingales are results on stable convergence to a mixed normal limit with an unknown conditional variance. Estimating this conditional variance usually is a hard task, in particular when the underlying process contains jumps. For this reason, several authors have recently discussed methods to automatically estimate the conditional variance, i.e. they build a consistent estimator from the original statistics, but computed at different time scales. Their methods work in several situations, but are essentially restricted to the case of continuous paths always. The aim of this work is to present a new method to consistently estimate the conditional variance which works regardless of whether the underlying process is continuous or has jumps. We will discuss the case of power variations in detail and give insight to the heuristics behind the approach.

     

How to estimate the value of a series in the ratio test

<正>We’ll learn about how to estimate the values of the series which is convergent by the ratio test.Assume the series∑a_n,and each term is positive,and it is convergent by testing the Ratio Test,so we know L=a_(n+1)/a_n<1.Let R_n be the remainder.Let the partial sum be S_n     

Multiple attractors and crisis route to chaos in a model food-chain

An attempt has been made to identify the mechanism, which is responsible for the existence of chaos in narrow parameter range in a realistic ecological model food-chain. Analytical and numerical studies of a three species food-chain model similar to a situation likely to be seen in terrestrial ecosystems has been carried out. The study of the model food chain suggests that the existence of chaos in narrow parameter ranges is caused by the crisis-induced sudden death of chaotic attractors. Varying one of the critical parameters in its range while keeping all the others constant, one can monitor the changes in the dynamical behaviour of the system, thereby fixing the regimes in which the system exhibits chaotic dynamics. The computed bifurcation diagrams and basin boundary calculations indicate that crisis is the underlying factor which generates chaotic dynamics in this model food-chain. We investigate sudden qualitative changes in chaotic dynamical behaviour, which occur at a parameter value a₁=1.7804 at which the chaotic attractor destroyed by boundary crisis with an unstable periodic orbit created by the saddle-node bifurcation. Multiple attractors with riddled basins and fractal boundaries are also observed. If ecological systems of interacting species do indeed exhibit multiple attractors etc., the long term dynamics of such systems may undergo vast qualitative changes following epidemics or environmental catastrophes due to the system being pushed into the basin of a new attractor by the perturbation. Coupled with stochasticity, such complex behaviours may render such systems practically unpredictable.