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Abstract.We use data from a recent long ASCA observation of the Narrow Line Seyfert 1 galaxy Ark 564 to investigate in detail its timing properties. We show that a thorough analysis of the time series, employing techniques not generally applied to AGN light curves, can provide useful information to characterize the engines of these powerful sources. We searched for signs of non-stationarity in the data, but did not find strong evidences for it. We find that the process causing the variability is very likely nonlinear, suggesting that variability models based on many active regions, as the shot noise model, may not be applicable to Ark 564. The complex light curve can be viewed, for a limited range of time scales (as indicated by the breaks in the structure and power density spectrum), as a fractal object with non-trivial fractal dimension and statistical self-similarity. Finally, using a nonlinear statistic based on the scaling index as a tool to discriminate time series, we demonstrate that the high and low count rate states, which are indistinguishable on the basis of their autocorrelation, structure and probability density functions, are intrinsically different, with the high state characterized by higher complexity.

Observations of the behavior of a multimode continuous-wave dye laser around instabilities are interpreted using the concept of pragmatic information. It is demonstrated that this concept contains aspects of two different approaches toward the description of self-organizing system, namely, those of synergetics and of nonequilibrium thermodynamics. Both of them prove to be particularly relevant in the considered example. The key quantities of the two approaches (efficiency and entropy production) are related to a measure of pragmatic information. The significance of this measure for general issues referring to meaning, complexity, and evolution in self-organizing processes is indicated.

Two-dimensional coupled map lattices have global stability properties that depend on the coupling between individual maps and their neighborhood. The action of the neighborhood on individual maps can be implemented in terms of "causal" coupling (to spatially distant past states) or "non-causal" coupling (to spatially distant simultaneous states). In this contribution we show that globally stable behavior of coupled map lattices is facilitated by causal coupling, thus indicating a surprising relationship between stability and causality. The influence of causal versus non-causal coupling for synchronous and asynchronous updating as a function of coupling strength and for different neighborhoods is analyzed in detail.