Much of what is known about specific dynamical systems is obtained from numerical experiments. Although the discretization process usually has no significant effect on the results for simple, well-behaved dynamics, acute sensitivity to changes in initial conditions is a hallmark of chaotic behavior. How confident can one be that the numerical dynamics reflects that of the original system? Do numerically calculated trajectories always shadow a true one? What role does numerical analysis play in the study of dynamical systems? And conversely, can advances in dynamical systems provide new insights into numerical algorithms? These and related issues were the focus of the workshop on Chaotic Numerics, held at Deakin University in Geelong, Australia, in July 1993. The contributions to this book are based on lectures presented during the workshop and provide a broad overview of this area of research.

In this book the theory of hyperbolic sets is developed, both for diffeomorphisms and flows, with an emphasis on shadowing. We show that hyperbolic sets are expansive and have the shadowing property. Then we use shadowing to prove that hyperbolic sets are robust under perturbation, that they have an asymptotic phase property and also that the dynamics near a transversal homoclinic orbit is chaotic. It turns out that chaotic dynamical systems arising in practice are not quite hyperbolic. However, they possess enough hyperbolicity to enable us to use shadowing ideas to give computer-assisted proofs that computed orbits of such systems can be shadowed by true orbits for long periods of time, that they possess periodic orbits of long periods and that it is really true that they are chaotic. Audience: This book is intended primarily for research workers in dynamical systems but could also be used in an advanced graduate course taken by students familiar with calculus in Banach spaces and with the basic existence theory for ordinary differential equations.

It is now generally recognised that very simple dynamical systems can produce apparently random behaviour. In the last couple of years, attention has turned to focus on the flip side of this coin: random-looking time series (or random-looking patterns in space) may indeed be the result of very complicated processes or “real noise”, but they may equally well be produced by some very simple mechanism (a low-dimensional attractor). In either case, a long-term prediction will be possible only in probabilistic terms. However, in the very short term, random systems will still be unpredictable but low-dimensional chaotic ones may be predictable (appearances to the contrary). The Royal Society held a two-day discussion meeting on topics covering diverse fields, including biology, economics, geophysics, meteorology, statistics, epidemiology, earthquake science and many others. Each topic was covered by a leading expert in the field. The meeting dealt with different basic approaches to the problem of chaos and forecasting, and covered applications to nonlinear forecasting of both artificially-generated time series and real data from context in the above-mentioned diverse fields. This book marks a rather special and rare occasion on which prominent scientists from different areas converge on the same theme. It forms an informative introduction to the science of chaos, with special reference to real data.

Market: Students and researchers in chaos, plasma physics, and fluid transport. This superb collection of invited papers offers an excellent overview of the current status and future trends in chaotic dynamics, plasma and fluid physics, nonlinear phenomena and chaos, and transport and turbulence studies.