Directional complexity and entropy for lift mappings

We introduce and study the notion of a directional complexity and entropy for maps of degree 1 on the circle. For piecewise affine Markov maps we use symbolic dynamics to relate this complexity to the symbolic complexity. We apply a combinatorial machinery to obtain exact formulas for the directional entropy, to find the maximal directional entropy, and to show that it equals the topological entropy of the map. Keywords: Rotation interval, Space-time window, Directional complexity, Directional entropy;Comment: 19p. 3 fig, Discrete and Continuous Dynamical Systems-B (Vol. 20, No. 10) December 201

On the statistical distribution of first--return times of balls and cylinders in chaotic systems

We study returns in dynamical systems: when a set of points, initially populating a prescribed region, swarms around phase space according to a deterministic rule of motion, we say that the return of the set occurs at the earliest moment when one of these points comes back to the original region. We describe the statistical distribution of these "first--return times" in various settings: when phase space is composed of sequences of symbols from a finite alphabet (with application for instance to biological problems) and when phase space is a one and a two-dimensional manifold. Specifically, we consider Bernoulli shifts, expanding maps of the interval and linear automorphisms of the two dimensional torus. We derive relations linking these statistics with Renyi entropies and Lyapunov exponents.Comment: submitted to Int. J. Bifurcations and Chao

Existence and Stability of Steady Fronts in Bistable CML

We prove the existence and we study the stability of the kink-like fixed points in a simple Coupled Map Lattice for which the local dynamics has two stable fixed points. The condition for the existence allows us to define a critical value of the coupling parameter where a (multi) generalized saddle-node bifurcation occurs and destroys these solutions. An extension of the results to other CML's in the same class is also displayed. Finally, we emphasize the property of spatial chaos for small coupling.Comment: 18 pages, uuencoded PostScript file, J. Stat. Phys. (In press

Detectability of non-differentiable generalized synchrony

Generalized synchronization of chaos is a type of cooperative behavior in directionally-coupled oscillators that is characterized by existence of stable and persistent functional dependence of response trajectories from the chaotic trajectory of driving oscillator. In many practical cases this function is non-differentiable and has a very complex shape. The generalized synchrony in such cases seems to be undetectable, and only the cases, in which a differentiable synchronization function exists, are considered to make sense in practice. We show that this viewpoint is not always correct and the non-differentiable generalized synchrony can be revealed in many practical cases. Conditions for detection of generalized synchrony are derived analytically, and illustrated numerically with a simple example of non-differentiable generalized synchronization.Comment: 8 pages, 8 figures, submitted to PR

Adaptive coupling for achieving stable synchronization of chaos

We consider synchronization of coupled chaotic systems and propose an adaptive strategy that aims at evolving the strength of the coupling to achieve stability of the synchronized evolution. We test this idea in a simple configuration in which two chaotic systems are unidirectionally coupled (a sender and a receiver) and we study conditions for the receiver to adaptively synchronize with the sender. Numerical simulations show that, under certain conditions, our strategy is successful in dynamically evolving the coupling strength until it converges to a value that is compatible with synchronization.Comment: 12 Pages, 9 figures, accepted for publication in Physical Review

The shock-acoustic waves generated by earthquakes

We investigate the form and dynamics of shock-acoustic waves generated by earthquakes. We use the method for detecting and locating the sources of ionospheric impulsive disturbances, based on using data from a global network of receivers of the GPS navigation system and requiring no a priori information about the place and time of associated effects. The practical implementation of the method is illustrated by a case study of earthquake effects in Turkey (August 17, and November 12, 1999), in Southern Sumatera (June 4, 2000), and off the coast of Central America (January 13, 2001). It was found that in all instances the time period of the ionospheric response is 180-390 s, and the amplitude exceeds by a factor of two as a minimum the standard deviation of background fluctuations in total electron content in this range of periods under quiet and moderate geomagnetic conditions. The elevation of the wave vector varies through a range of 20-44 degree, and the phase velocity (1100-1300 m/s) approaches the sound velocity at the heights of the ionospheric F-region maximum. The calculated (by neglecting refraction corrections) location of the source roughly corresponds to the earthquake epicenter. Our data are consistent with the present views that shock-acoustic waves are caused by a piston-like movement of the Earth surface in the zone of an earthquake epicenter.Comment: EmTeX-386, 30 pages, 4 figures, 3 tabl

Superdiffusion in the Dissipative Standard Map

We consider transport properties of the chaotic (strange) attractor along unfolded trajectories of the dissipative standard map. It is shown that the diffusion process is normal except of the cases when a control parameter is close to some special values that correspond to the ballistic mode dynamics. Diffusion near the related crisises is anomalous and non-uniform in time: there are large time intervals during which the transport is normal or ballistic, or even superballistic. The anomalous superdiffusion seems to be caused by stickiness of trajectories to a non-chaotic and nowhere dense invariant Cantor set that plays a similar role as cantori in Hamiltonian chaos. We provide a numerical example of such a sticky set. Distribution function on the sticky set almost coincides with the distribution function (SRB measure) of the chaotic attractor.Comment: 10 Figure