Overview
- Exercises included
- Readers can easily extract basic idea underlying each approach
- Written for graduate students in graph theory
Part of the book series: Applied Mathematical Sciences (AMS, volume 211)
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Table of contents (13 chapters)
Keywords
About this book
This book is intended to provide graduate students and researchers in graph theory with an overview of the elementary methods of graph Ramsey theory. It is especially targeted towards graduate students in extremal graph theory, graph Ramsey theory, and related fields, as the included contents allow the text to be used in seminars.
It is structured in thirteen chapters which are application-focused and largely independent, enabling readers to target specific topics and information to focus their study. The first chapter includes a true beginner’s overview of elementary examples in graph Ramsey theory mainly using combinatorial methods. The following chapters progress through topics including the probabilistic methods, algebraic construction, regularity method, but that's not all.Many related interesting topics are also included in this book, such as the disproof for a conjecture of Borsuk on geometry, intersecting hypergraphs, Turán numbers and communication channels, etc.
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Bibliographic Information
Book Title: Elementary Methods of Graph Ramsey Theory
Authors: Yusheng Li, Qizhong Lin
Series Title: Applied Mathematical Sciences
DOI: https://doi.org/10.1007/978-3-031-12762-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-031-12761-8Published: 17 September 2022
Softcover ISBN: 978-3-031-12764-9Published: 18 September 2023
eBook ISBN: 978-3-031-12762-5Published: 16 September 2022
Series ISSN: 0066-5452
Series E-ISSN: 2196-968X
Edition Number: 1
Number of Pages: XIII, 346
Number of Illustrations: 10 b/w illustrations
Topics: Graph Theory, Discrete Mathematics, Probability Theory and Stochastic Processes