
Superconcentration and Related Topics
Sourav Chatterjee(Author)
Springer (Publisher)
Published on 22. January 2014
Book
Hardback
IX, 156 pages
978-3-319-03885-8 (ISBN)
Description
A certain curious feature of random objects, introduced by the author as "super concentration," and two related topics, "chaos" and "multiple valleys," are highlighted in this book. Although super concentration has established itself as a recognized feature in a number of areas of probability theory in the last twenty years (under a variety of names), the author was the first to discover and explore its connections with chaos and multiple valleys. He achieves a substantial degree of simplification and clarity in the presentation of these findings by using the spectral approach.
Understanding the fluctuations of random objects is one of the major goals of probability theory and a whole subfield of probability and analysis, called concentration of measure, is devoted to understanding these fluctuations. This subfield offers a range of tools for computing upper bounds on the orders of fluctuations of very complicated random variables. Usually, concentration of measure is useful when more direct problem-specific approaches fail; as a result, it has massively gained acceptance over the last forty years. And yet, there is a large class of problems in which classical concentration of measure produces suboptimal bounds on the order of fluctuations. Here lies the substantial contribution of this book, which developed from a set of six lectures the author first held at the Cornell Probability Summer School in July 2012.
The book is interspersed with a sizable number of open problems for professional mathematicians as well as exercises for graduate students working in the fields of probability theory and mathematical physics. The material is accessible to anyone who has attended a graduate course in probability.
Understanding the fluctuations of random objects is one of the major goals of probability theory and a whole subfield of probability and analysis, called concentration of measure, is devoted to understanding these fluctuations. This subfield offers a range of tools for computing upper bounds on the orders of fluctuations of very complicated random variables. Usually, concentration of measure is useful when more direct problem-specific approaches fail; as a result, it has massively gained acceptance over the last forty years. And yet, there is a large class of problems in which classical concentration of measure produces suboptimal bounds on the order of fluctuations. Here lies the substantial contribution of this book, which developed from a set of six lectures the author first held at the Cornell Probability Summer School in July 2012.
The book is interspersed with a sizable number of open problems for professional mathematicians as well as exercises for graduate students working in the fields of probability theory and mathematical physics. The material is accessible to anyone who has attended a graduate course in probability.
More details
Product info
Book
Series
Language
English
Place of publication
Cham
Switzerland
Target group
Research
Product notice
Laminated cover
Illustrations
Bibliographie
Dimensions
Height: 242 mm
Width: 164 mm
Thickness: 17 mm
Weight
398 gr
ISBN-13
978-3-319-03885-8 (9783319038858)
DOI
10.1007/978-3-319-03886-5
Schweitzer Classification
Other editions
Additional editions

Sourav Chatterjee
Superconcentration and Related Topics
Book
08/2016
1st Edition
Springer
€106.99
Shipment within 10-15 days

Sourav Chatterjee
Superconcentration and Related Topics
E-Book
01/2014
1st Edition
Springer
€96.29
Available for download
Person
Sourav Chatterjee is a Professor of Statistics and Mathematics at Stanford University. He has previously taught at the University of California at Berkeley and at the Courant Institute of Mathematical Sciences. He has won several international awards for his work in probability theory, including the Rollo Davidson Prize (2010), the Doeblin Prize (2012) and the Loève Prize (2013) and has received the invitation to speak at the International Congress of Mathematicians in 2014.
Content
Preface.- 1.Introduction.- 2.Markov semigroups.- 3.Super concentration and chaos.- 4.Multiple valleys.- 5.Talagrand's method for proving super concentration.- 6.The spectral method for proving super concentration.- 7.Independent flips.- 8.Extremal fields.- 9.Further applications of hypercontractivity.- 10.The interpolation method for proving chaos.- 11.Variance lower bounds.- 12.Dimensions of level sets.- Appendix A. Gaussian random variables.- Appendix B. Hypercontractivity.- Bibliography.- Indices.