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Guide to First-Passage Processes

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ISBN-10: 0521036917

ISBN-13: 9780521036917

Edition: 2007

Authors: Sidney Redner

List price: $69.99
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Description:

First-passage properties underlie a wide range of stochastic processes, such as diffusion-limited growth, neuron firing, and the triggering of stock options. This book provides a unified presentation of first-passage processes, which highlights its interrelations with electrostatics and the resulting powerful consequences. The author begins with a modern presentation of fundamental theory including the connection between the occupation and first-passage probabilities of a random walk, and the connection to electrostatics and current flows in resistor networks. The consequences of this theory are then developed for simple, illustrative geometries including the finite and semi-infinite…    
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Book details

List price: $69.99
Copyright year: 2007
Publisher: Cambridge University Press
Publication date: 5/15/2007
Binding: Paperback
Pages: 328
Size: 5.98" wide x 9.02" long x 0.75" tall
Weight: 1.056
Language: English

Sid Redner is a condensed-matter theorist whose research focuses on non-equilibrium statistical physics and its applications. Dr Redner has been on the physics faculty at Boston University since 1978 and has been a full professor since 1989. He has published 230 research articles and is the author of A Kinetic View of Statistical Physics with P. L. Krapivsky and E. Ben-Naim (Cambridge University Press, 2010). Dr Redner is a Fellow of the American Physical Society and was a visiting scientist at Schlumberger Research in 1984 1985, the Ulam Scholar at Los Alamos National Laboratory in 2004 2005 and a visiting professor at the Universite Paul Sabatier (Toulouse) and Universite Pierre et Marie…    

Preface
Errata
First-passage fundamentals
First passage in an interval
Semi-infinite system
Illustrations of first passage in simple geometries
Fractal and nonfractal networks
Systems with spherical symmetry
Wedge domains
Applications to simple reactions
References
Index