Large Deviations for Random Graphs

Large Deviations for Random Graphs

Author: Sourav Chatterjee

Publisher: Springer

Published: 2017-08-31

Total Pages: 175

ISBN-13: 3319658166

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This book addresses the emerging body of literature on the study of rare events in random graphs and networks. For example, what does a random graph look like if by chance it has far more triangles than expected? Until recently, probability theory offered no tools to help answer such questions. Important advances have been made in the last few years, employing tools from the newly developed theory of graph limits. This work represents the first book-length treatment of this area, while also exploring the related area of exponential random graphs. All required results from analysis, combinatorics, graph theory and classical large deviations theory are developed from scratch, making the text self-contained and doing away with the need to look up external references. Further, the book is written in a format and style that are accessible for beginning graduate students in mathematics and statistics.


Random Graphs and Complex Networks

Random Graphs and Complex Networks

Author: Remco van der Hofstad

Publisher: Cambridge University Press

Published: 2017

Total Pages: 341

ISBN-13: 110717287X

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This classroom-tested text is the definitive introduction to the mathematics of network science, featuring examples and numerous exercises.


Introduction to Random Graphs

Introduction to Random Graphs

Author: Alan Frieze

Publisher: Cambridge University Press

Published: 2016

Total Pages: 483

ISBN-13: 1107118506

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The text covers random graphs from the basic to the advanced, including numerous exercises and recommendations for further reading.


Random Graph Dynamics

Random Graph Dynamics

Author: Rick Durrett

Publisher: Cambridge University Press

Published: 2010-05-31

Total Pages: 203

ISBN-13: 1139460889

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The theory of random graphs began in the late 1950s in several papers by Erdos and Renyi. In the late twentieth century, the notion of six degrees of separation, meaning that any two people on the planet can be connected by a short chain of people who know each other, inspired Strogatz and Watts to define the small world random graph in which each site is connected to k close neighbors, but also has long-range connections. At a similar time, it was observed in human social and sexual networks and on the Internet that the number of neighbors of an individual or computer has a power law distribution. This inspired Barabasi and Albert to define the preferential attachment model, which has these properties. These two papers have led to an explosion of research. The purpose of this book is to use a wide variety of mathematical argument to obtain insights into the properties of these graphs. A unique feature is the interest in the dynamics of process taking place on the graph in addition to their geometric properties, such as connectedness and diameter.


Large random matrices

Large random matrices

Author: Alice Guionnet

Publisher: Springer Science & Business Media

Published: 2009-03-25

Total Pages: 296

ISBN-13: 3540698965

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These lectures emphasize the relation between the problem of enumerating complicated graphs and the related large deviations questions. Such questions are closely related with the asymptotic distribution of matrices.


Probability on Graphs

Probability on Graphs

Author: Geoffrey Grimmett

Publisher: Cambridge University Press

Published: 2018-01-25

Total Pages: 279

ISBN-13: 1108542999

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This introduction to some of the principal models in the theory of disordered systems leads the reader through the basics, to the very edge of contemporary research, with the minimum of technical fuss. Topics covered include random walk, percolation, self-avoiding walk, interacting particle systems, uniform spanning tree, random graphs, as well as the Ising, Potts, and random-cluster models for ferromagnetism, and the Lorentz model for motion in a random medium. This new edition features accounts of major recent progress, including the exact value of the connective constant of the hexagonal lattice, and the critical point of the random-cluster model on the square lattice. The choice of topics is strongly motivated by modern applications, and focuses on areas that merit further research. Accessible to a wide audience of mathematicians and physicists, this book can be used as a graduate course text. Each chapter ends with a range of exercises.


Random Graphs and Complex Networks

Random Graphs and Complex Networks

Author: Remco van der Hofstad

Publisher: Cambridge University Press

Published: 2024-02-08

Total Pages: 507

ISBN-13: 1107174007

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The definitive introduction to the local and global structure of random graph models for complex networks.


Large Deviations and Applications

Large Deviations and Applications

Author: S. R. S. Varadhan

Publisher: SIAM

Published: 1984-01-31

Total Pages: 74

ISBN-13: 0898711894

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Many situations exist in which solutions to problems are represented as function space integrals. Such representations can be used to study the qualitative properties of the solutions and to evaluate them numerically using Monte Carlo methods. The emphasis in this book is on the behavior of solutions in special situations when certain parameters get large or small.


High-Dimensional Probability

High-Dimensional Probability

Author: Roman Vershynin

Publisher: Cambridge University Press

Published: 2018-09-27

Total Pages: 299

ISBN-13: 1108415199

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An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.


Particle Systems, Random Media and Large Deviations

Particle Systems, Random Media and Large Deviations

Author: Richard Durrett

Publisher: American Mathematical Soc.

Published: 1985

Total Pages: 394

ISBN-13: 0821850423

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Covers the proceedings of the 1984 AMS Summer Research Conference. This work provides a summary of results from some of the areas in probability theory; interacting particle systems, percolation, random media (bulk properties and hydrodynamics), the Ising model and large deviations.