Abstract:
Strange nonchaotic attractors (SNAs), which are realized in many quasiperiodically driven nonlinear systems are strange (geometrically fractal) but nonchaotic (the largest nontrivial Lyapunov exponent is negative). Two such identical independent systems can be synchronized by in-phase driving: because of the negative Lyapunov exponent, the systems converge to a common dynamics which, because of the strangeness of the underlying attractor, is aperiodic. This feature, which is robust to external noise, can be used for applications such as secure communication. A possible implementation is discussed, and its performance is evaluated. The use of SNAs rather than chaotic attractors can offer some advantages in experiments involving synchronization with aperiodic dynamics.

Abstract:
We study three models of driven sandpile-type automata in the presence of quenched random defects. When the dynamics is conservative, all these models, termed the random sites (A), random bonds (B), and random slopes (C), self-organize into a critical state. For Model C the concentration-dependent exponents are nonuniversal. In the case of nonconservative defects, the asymptotic state is subcritical. Possible defect-mediated nonequilibrium phase transitions are also discussed.

Abstract:
We study the variation of Lyapunov exponents of simple dynamical systems near attractor-widening and attractor-merging crises. The largest Lyapunov exponent has universal behaviour, showing abrupt variation as a function of the control parameter as the system passes through the crisis point, either in the value itself, in the case of the attractor-widening crisis, or in the slope, for attractor merging crises. The distribution of local Lyapunov exponents is very different for the two cases: the fluctuations remain constant through a merging crisis, but there is a dramatic increase in the fluctuations at a widening crisis.

Abstract:
We study a directed coupled map lattice model in two dimensions, with two degrees of freedom associated with each lattice site. The two freedoms are coupled at a fraction $c$ of lattice bonds acting as quenched random defects. In the case of conservative dynamics, at any concentration of defects the system reaches a self-organized critical state with universal critical exponents close to the mean-field values. The probability distributions follow the general scaling form $P(X,L)= L^{-\alpha}{\cal{P}}(XL^{-D_X})$, where $\alpha \approx 1$ is the scaling exponent for the distribution of avalanche lengths, $X$ stands for duration, size or released energy, and $D_X$ is the fractal dimension with respect to $X$. The distribution of current is nonuniversal, and does not show any apparent scaling form. In the case of nonconservative dynamics---obtained by incomplete energy transfer at the defect bonds--- the system is driven out of the critical state. In the scaling region close to $c=0$ the probability distributions exhibit the general scaling form $P(X,c,L)=X^{-\tau _X }{\cal{P}}(X/\xi _X (c), XL^{-D_X})$, where $\tau _X =\alpha /D_X$ and the coherence length $\xi_X (c)$ depends on the concentration of defect bonds $c$ as $\xi _X (c)\sim c^{-D_X}$.

Abstract:
Upon addition of noise, chaotic motion in low-dimensional dynamical systems can sometimes be transformed into nonchaotic dynamics: namely, the largest Lyapunov exponent can be made nonpositive. We study this phenomenon in model systems with a view to understanding the circumstances when such behaviour is possible. This technique for inducing ``order'' through stochastic driving works by modifying the invariant measure on the attractor: by appropriately increasing measure on those portions of the attractor where the dynamics is contracting, the overall dynamics can be made nonchaotic, however {\it not} a strange nonchaotic attractor. Alternately, by decreasing measure on contracting regions, the largest Lyapunov exponent can be enhanced. A number of different chaos control and anticontrol techniques are known to function on this paradigm.

Abstract:
We calculate the maximal Lyapunov exponent in constant-energy molecular dynamics simulations at the melting transition for finite clusters of 6 to 13 particles (model rare-gas and metallic systems) as well as for bulk rare-gas solid. For clusters, the Lyapunov exponent generally varies linearly with the total energy, but the slope changes sharply at the melting transition. In the bulk system, melting corresponds to a jump in the Lyapunov exponent, and this corresponds to a singularity in the variance of the curvature of the potential energy surface. In these systems there are two mechanisms of chaos -- local instability and parametric instability. We calculate the contribution of the parametric instability towards the chaoticity of these systems using a recently proposed formalism. The contribution of parametric instability is a continuous function of energy in small clusters but not in the bulk where the melting corresponds to a decrease in this quantity. This implies that the melting in small clusters does not lead to enhanced local instability.

Abstract:
The probability distribution of finite-time Lyapunov exponents provides an important characterization of dynamical attractors. We study such distributions for strange nonchaotic attractors (SNAs) created through several different mechanisms in quasiperiodically forced nonlinear dynamical systems. Statistical properties of the distributions such as the variance and the skewness also distinguish between SNAs formed by different bifurcation routes.

Abstract:
We study the probability densities of finite-time or \local Lyapunov exponents (LLEs) in low-dimensional chaotic systems. While the multifractal formalism describes how these densities behave in the asymptotic or long-time limit, there are significant finite-size corrections which are coordinate dependent. Depending on the nature of the dynamical state, the distribution of local Lyapunov exponents has a characteristic shape. For intermittent dynamics, and at crises, dynamical correlations lead to distributions with stretched exponential tails, while for fully-developed chaos the probability density has a cusp. Exact results are presented for the logistic map, $x \to 4x(1-x)$. At intermittency the density is markedly asymmetric, while for `typical' chaos, it is known that the central limit theorem obtains and a Gaussian density results. Local analysis provides information on the variation of predictability on dynamical attractors. These densities, which are used to characterize the {\sl nonuniform} spatial organization on chaotic attractors are robust to noise and can therefore be measured from experimental data.

Abstract:
We show that it is possible to devise a large class of skew--product dynamical systems which have strange nonchaotic attractors (SNAs): the dynamics is asymptotically on fractal attractors and the largest Lyapunov exponent is nonpositive. Furthermore, we show that quasiperiodic forcing, which has been a hallmark of essentially allhitherto known examples of such dynamics is {\it not} necessary for the creation of SNAs.

Abstract:
Localized states of Harper's equation correspond to strange nonchaotic attractors (SNAs) in the related Harper mapping. In parameter space, these fractal attractors with nonpositive Lyapunov exponents occur in fractally organized tongue--like regions which emanate from the Cantor set of eigenvalues on the critical line $\epsilon = 1$. A topological invariant characterizes wavefunctions corresponding to energies in the gaps in the spectrum. This permits a unique integer labeling of the gaps and also determines their scaling properties as a function of potential strength.