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A hundred years ago it became known that deterministic systems can
exhibit very complex behavior. By proving that ordinary
differential equations can exhibit strange behavior, Poincare
undermined the founda tions of Newtonian physics and opened a
window to the modern theory of nonlinear dynamics and chaos.
Although in the 1930s and 1940s strange behavior was observed in
many physical systems, the notion that this phenomenon was inherent
in deterministic systems was never suggested. Even with the
powerful results of S. Smale in the 1960s, complicated be havior of
deterministic systems remained no more than a mathematical
curiosity. Not until the late 1970s, with the advent of fast and
cheap comput ers, was it recognized that chaotic behavior was
prevalent in almost all domains of science and technology. Smale
horseshoes began appearing in many scientific fields. In 1971, the
phrase 'strange attractor' was coined to describe complicated
long-term behavior of deterministic systems, and the term quickly
became a paradigm of nonlinear dynamics. The tools needed to study
chaotic phenomena are entirely different from those used to study
periodic or quasi-periodic systems; these tools are analytic and
measure-theoretic rather than geometric. For example, in throwing a
die, we can study the limiting behavior of the system by viewing
the long-term behavior of individual orbits. This would reveal
incomprehensibly complex behavior. Or we can shift our perspective:
Instead of viewing the long-term outcomes themselves, we can view
the probabilities of these outcomes. This is the measure-theoretic
approach taken in this book."
A hundred years ago it became known that deterministic systems can
exhibit very complex behavior. By proving that ordinary
differential equations can exhibit strange behavior, Poincare
undermined the founda tions of Newtonian physics and opened a
window to the modern theory of nonlinear dynamics and chaos.
Although in the 1930s and 1940s strange behavior was observed in
many physical systems, the notion that this phenomenon was inherent
in deterministic systems was never suggested. Even with the
powerful results of S. Smale in the 1960s, complicated be havior of
deterministic systems remained no more than a mathematical
curiosity. Not until the late 1970s, with the advent of fast and
cheap comput ers, was it recognized that chaotic behavior was
prevalent in almost all domains of science and technology. Smale
horseshoes began appearing in many scientific fields. In 1971, the
phrase 'strange attractor' was coined to describe complicated
long-term behavior of deterministic systems, and the term quickly
became a paradigm of nonlinear dynamics. The tools needed to study
chaotic phenomena are entirely different from those used to study
periodic or quasi-periodic systems; these tools are analytic and
measure-theoretic rather than geometric. For example, in throwing a
die, we can study the limiting behavior of the system by viewing
the long-term behavior of individual orbits. This would reveal
incomprehensibly complex behavior. Or we can shift our perspective:
Instead of viewing the long-term outcomes themselves, we can view
the probabilities of these outcomes. This is the measure-theoretic
approach taken in this book."
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