Elementary Methods of Graph Ramsey Theory / by Yusheng Li, Qizhong Lin.

Author
Li, Yusheng [Browse]
Format
Book
Language
English
Εdition
1st ed. 2022.
Published/​Created
Cham : Springer International Publishing : Imprint: Springer, 2022.
Description
1 online resource (349 pages)

Details

Subject(s)
Author
Series
Summary note
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.
Bibliographic references
Includes bibliographical references and index.
Contents
  • Existence
  • Small Ramsey Numbers
  • Basic Probalistic Method
  • Random Graph
  • Lovász Local Lemma
  • Constructive Lower Bounds
  • Turán Number and Related Ramsey Number
  • Communication Channels
  • Dependent Random Choice
  • Quasi-Random Graphs
  • Regularity Lemma and van der Waerden Number
  • More Ramsey Linear Functions
  • Various Ramsey Problems.
ISBN
3-031-12762-5
Doi
  • 10.1007/978-3-031-12762-5
Statement on responsible collection description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage. Read more...
Other views
Staff view

Supplementary Information