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Ergodic Theory Via Joinings.
・ISBN 978-1-4704-1951-6 paper US$ 98.00
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| 著者・編者 | Glasner, Eli, |
|---|---|
| シリーズ | Mathematical Surveys and Monographs |
| 出版社 | (American Mathematical Society, US) |
| 出版年月 | 2015 |
| ページ数 | 384 pp. |
| 言語 | ENG |
| ニュース番号 | ＜M25-16414＞ |
解説
This book is an introduction to modern ergodic theory. It emphasizes a new approach that relies on the technique of joining two (or more) dynamical systems. This approach has proved to be fruitful in many recent works, and this is the first time that the entire theory is presented from a joining perspective.
Another new feature of the book is the presentation of basic definitions of ergodic theory in terms of the Koopman unitary representation associated with a dynamical system and the invariant mean on matrix coefficients, which exists for any acting groups, amenable or not. Accordingly, the first part of the book treats the ergodic theory for an action of an arbitrary countable group.
The second part, which deals with entropy theory, is confined (for the sake of simplicity) to the classical case of a single measure-preserving transformation on a Lebesgue probability space.
The book is intended for graduate students who have a good command of basic measure theory and functional analysis and who would like to master the subject. It contains many detailed examples and many exercises, usually with indications of solutions. It can serve equally well as a textbook for graduate courses or as a streamlined introduction for non-specialists who wish to learn about modern aspects of ergodic theory.
Another new feature of the book is the presentation of basic definitions of ergodic theory in terms of the Koopman unitary representation associated with a dynamical system and the invariant mean on matrix coefficients, which exists for any acting groups, amenable or not. Accordingly, the first part of the book treats the ergodic theory for an action of an arbitrary countable group.
The second part, which deals with entropy theory, is confined (for the sake of simplicity) to the classical case of a single measure-preserving transformation on a Lebesgue probability space.
The book is intended for graduate students who have a good command of basic measure theory and functional analysis and who would like to master the subject. It contains many detailed examples and many exercises, usually with indications of solutions. It can serve equally well as a textbook for graduate courses or as a streamlined introduction for non-specialists who wish to learn about modern aspects of ergodic theory.