Cover image for Computational ergodic theory
Title:
Computational ergodic theory
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Series:
Algorithms and computation in mathematics ; 13
Publication Information:
Berlin : Springer, 2005
ISBN:
9783540231219

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30000010103705 QA313 C46 2005 Open Access Book Book
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Summary

Summary

Ergodic theory is hard to study because it is based on measure theory, which is a technically difficult subject to master for ordinary students, especially for physics majors. Many of the examples are introduced from a different perspective than in other books and theoretical ideas can be gradually absorbed while doing computer experiments. Theoretically less prepared students can appreciate the deep theorems by doing various simulations. The computer experiments are simple but they have close ties with theoretical implications. Even the researchers in the field can benefit by checking their conjectures, which might have been regarded as unrealistic to be programmed easily, against numerical output using some of the ideas in the book. One last remark: The last chapter explains the relation between entropy and data compression, which belongs to information theory and not to ergodic theory. It will help students to gain an understanding of the digital technology that has shaped the modern information society.


Table of Contents

Prerequisites
Invariant Measures
The Birkhoff Ergodic Theorem
The Central Limit Theorem
More on Ergodicity
Homeomorphisms of the Circle
Mod 2 Uniform Distribution
Entropy
The Lyapunov Exponent: One-dimensional Case
The Lyapunov Exponent: Multidimensional Case
Stable and Unstable Manifolds
Recurrence and Entropy
Recurrence and Dimension
Data Compression
References
Index