Fractal Properties of Robust Strange Nonchaotic Attractors in Maps of Two or More Dimensions

We consider the existence of robust strange nonchaotic attractors (SNA's) in a simple class of quasiperiodically forced systems. Rigorous results are presented demonstrating that the resulting attractors are strange in the sense that their box-counting dimension is N+1 while their information dimension is N. We also show how these properties are manifested in numerical experiments.Comment: 9 pages, 14 figure

Interruption of torus doubling bifurcation and genesis of strange nonchaotic attractors in a quasiperiodically forced map : Mechanisms and their characterizations

A simple quasiperiodically forced one-dimensional cubic map is shown to exhibit very many types of routes to chaos via strange nonchaotic attractors (SNAs) with reference to a two-parameter $(A-f)$ space. The routes include transitions to chaos via SNAs from both one frequency torus and period doubled torus. In the former case, we identify the fractalization and type I intermittency routes. In the latter case, we point out that atleast four distinct routes through which the truncation of torus doubling bifurcation and the birth of SNAs take place in this model. In particular, the formation of SNAs through Heagy-Hammel, fractalization and type--III intermittent mechanisms are described. In addition, it has been found that in this system there are some regions in the parameter space where a novel dynamics involving a sudden expansion of the attractor which tames the growth of period-doubling bifurcation takes place, giving birth to SNA. The SNAs created through different mechanisms are characterized by the behaviour of the Lyapunov exponents and their variance, by the estimation of phase sensitivity exponent as well as through the distribution of finite-time Lyapunov exponents.Comment: 27 pages, RevTeX 4, 16 EPS figures. Phys. Rev. E (2001) to appea

On the importance of the convergence to climate attractors

Ensemble approaches are becoming widely used in climate research. In contrast to weather forecast, however, in the climatic context one is interested in long-time properties, those arising on the scale of several decades. The well-known strong internal variability of the climate system implies the existence of a related dynamical attractor with chaotic properties. Under the condition of climate change this should be a snapshot attractor, naturally arising in an ensemble-based framework. Although ensemble averages can be evaluated at any instant of time, results obtained during the process of convergence of the ensemble towards the attractor are not relevant from the point of view of climate. In simulations, therefore, attention should be paid to whether the convergence to the attractor has taken place. We point out that this convergence is of exponential character, therefore, in a finite amount of time after initialization relevant results can be obtained. The role of the time scale separation due to the presence of the deep ocean is discussed from the point of view of ensemble simulations

Nonintegrable dynamics of the triplet-triplet spatiotemporal interaction

In this paper we examine the coupling of two wave triplets sharing two common modes. The analysis is performed in the solitonic sector of the parameter space where uncoupled solutions departing from linearly unstable homogeneous initial conditions evolve into a collection of regularly interspersed, spatiotemporally localized spikes. The uncoupled system is integrable, but coupling destroys integrability. As coupling grows, energy transfer to smaller spatial scales does appear and becomes faster not only in linearly unstable, but also in linearly stable cases. Chaos in low-dimensional subsystems appears to be responsible for the transfer. We perform a series of numerical tests to verify this idea

Pattern evolution in non-synchronizable scale-free networks

Pattern formation and evolution in the desynchronizing process of scale-free complex networks are investigated. Depending on how far the system is away from the synchronizable regime, two types of synchronous patterns are identified, namely, the giant-cluster state (GCS) and the scattered-cluster state (SCS). GCS is observed when a system is immediately outside of the synchronizable regime, where the dynamics undergoes a process of on-off intermittency and the patterns are signatured by the existence of a giant synchronous cluster. As the system leaves away from the synchronizable regime, GCS gradually transforms into SCS, accompanied by the continuous dissolving of the giant cluster. Both the two types of patterns are non-stationary, reflected as the timely changed size and content of the clusters. By introducing a new form of synchronization, the temporal phase synchronization, we investigate the dynamical and statistical properties of these non-stationary patterns. An interesting finding is that the unstable nodes of GCS, i.e. nodes that escape from the giant cluster more frequently, are independent of the coupling strength but are sensitive to the bifurcation types. The intermittent behavior of GCS is analyzed by a theory of snapshot attractors, and the theoretical predications fit the numerical observations qualitatively well