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A Crisanti

Publications and source records attributed to A Crisanti.

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Characterization of a periodically driven chaotic dynamical system

We discuss how to characterize the behavior of a chaotic dynamical system depending on a parameter that varies periodically in time. In particular, we study the predictability time, the correlations and the mean responses, by defining a local--in--time version of these quantities. In systems where the time scale related to the time periodic variation of the parameter is much larger than the ``internal'' time scale, one has that the local quantities strongly depend on the phase of the cycle. In this case, the standard global quantities can give misleading information.

chao-dyn

Sporadicity and synchronization in one-dimensional asymmetrically coupled maps

A one-dimensional chain of sporadic maps with asymmetric nearest neighbour couplings is numerically studied. It is shown that in the region of strong asymmetry the system becomes spatially fully synchronized, even in the thermodinamic limit, while the Lyapunov exponent is zero. For weak asymmetry the synchronization is no more complete, and the Lyapunov exponent becomes positive. In addition one has a clear relation between temporal and spatial chaos, {\it i.e.}: a positive effective Lyapunov exponent corresponds to a lack of synchronization and {\it vice versa}

cond-mat

One-dimensional asymmetrically coupled maps with defects

In this letter we study chaotic dynamical properties of an asymmetrically coupled one-dimensional chain of maps. We discuss the existence of coherent regions in terms of the presence of defects along the chain. We find out that temporal chaos is instantaneously localized around one single defect and that the tangent vector jumps from one defect to another in an apparently random way. We quantitatively measure the localization properties by defining an entropy-like function in the space of tangent vectors.

cond-mat

Products of Random Matrices for Disordered Systems

Products of random transfer matrices are applied to low dimensional disordered systems to evaluate numerically extensive quantities such as entropy and overlap probability distribution. The main advantage is the possibility to avoid numerical differentiation. The method works for arbitrary disorder distributions at any temperature.

cond-mat