Serge Cohen – författare

This volume contains the proceedings of the vVorkshop on Trees held in Versailles on 14-16 June 1995. Why: a workshop on trees? Two main reasons motivated this workshop. First, the current plethora of tree representations in branching processes which has be­ come obvious by the Minneapolis IMA Congress Classica] and Modern Branching Processes in 1994. But this would not have been sufficient to organize an "n-th" congress on branching processes. Secondly, regular discussions with researchers in algebra and computing sciences at the University of Versailles and at INRIA (lnstitut National de Recherche en Informatique et Automatique) convinced us it would be fruitful to offer the workers in these different fields the opportunity to exchange their points of view on the subject. The organizers being probabilists, a large part of the meeting (two sessions) was devoted t~ probability theor:y (not only branching processes). Nevertheless, the other three sessions focused on algorithms, on ultrametric and combinatorial aspects of trees and on disordered systems. Most papers in this volume are both of high level and of pedagogical interest. They are intended for a large public, including graduate students looking for an initiation to tree structures. The papers have been grouped into four sections: - disordered systems, - probability and trees, - large deviations, - ultrametric and algebraic aspects of trees. Some of the speakers are, unfortunately, not represented in this volume.

This volume contains the proceedings of the vVorkshop on Trees held in Versailles on 14-16 June 1995. Why: a workshop on trees? Two main reasons motivated this workshop. First, the current plethora of tree representations in branching processes which has be­ come obvious by the Minneapolis IMA Congress Classica] and Modern Branching Processes in 1994. But this would not have been sufficient to organize an "n-th" congress on branching processes. Secondly, regular discussions with researchers in algebra and computing sciences at the University of Versailles and at INRIA (lnstitut National de Recherche en Informatique et Automatique) convinced us it would be fruitful to offer the workers in these different fields the opportunity to exchange their points of view on the subject. The organizers being probabilists, a large part of the meeting (two sessions) was devoted t~ probability theor:y (not only branching processes). Nevertheless, the other three sessions focused on algorithms, on ultrametric and combinatorial aspects of trees and on disordered systems. Most papers in this volume are both of high level and of pedagogical interest. They are intended for a large public, including graduate students looking for an initiation to tree structures. The papers have been grouped into four sections: - disordered systems, - probability and trees, - large deviations, - ultrametric and algebraic aspects of trees. Some of the speakers are, unfortunately, not represented in this volume.

This is the second volume in a subseries of the Lecture Notes in Mathematics called Lévy Matters, which is published at irregular intervals over the years. Each volume examines a number of key topics in the theory or applications of Lévy processes and pays tribute to the state of the art of this rapidly evolving subject with special emphasis on the non-Brownian world. The expository articles in this second volume cover two important topics in the area of Lévy processes. The first article by Serge Cohen reviews the most important findings on fractional Lévy fields to date in a self-contained piece, offering a theoretical introduction as well as possible applications and simulation techniques. The second article, by Alexey Kuznetsov, Andreas E. Kyprianou, and Victor Rivero, presents an up to date account of the theory and application of scale functions for spectrally negative Lévy processes, including an extensive numerical overview.

This book focuses mainly on fractional Brownian fields and their extensions. It has been used to teach graduate students at Grenoble and Toulouse's Universities. It is as self-contained as possible and contains numerous exercises, with solutions in an appendix. After a foreword by Stéphane Jaffard, a long first chapter is devoted to classical results from stochastic fields and fractal analysis. A central notion throughout this book is self-similarity, which is dealt with in a second chapter with a particular emphasis on the celebrated Gaussian self-similar fields, called fractional Brownian fields after Mandelbrot and Van Ness's seminal paper. Fundamental properties of fractional Brownian fields are then stated and proved. The second central notion of this book is the so-called local asymptotic self-similarity (in short lass), which is a local version of self-similarity, defined in the third chapter. A lengthy study is devoted to lass fields with finite variance. Among these lass fields, we find both Gaussian fields and non-Gaussian fields, called Lévy fields. The Lévy fields can be viewed as bridges between fractional Brownian fields and stable self-similar fields. A further key issue concerns the identification of fractional parameters. This is the raison d'être of the statistics chapter, where generalized quadratic variations methods are mainly used for estimating fractional parameters. Last but not least, the simulation is addressed in the last chapter. Unlike the previous issues, the simulation of fractional fields is still an area of ongoing research. The algorithms presented in this chapter are efficient but do not claim to close the debate.

This book focuses mainly on fractional Brownian fields and their extensions. It has been used to teach graduate students at Grenoble and Toulouse''s Universities. It is as self-contained as possible and contains numerous exercises, with solutions in an appendix. After a foreword by Stéphane Jaffard, a long first chapter is devoted to classical results from stochastic fields and fractal analysis. A central notion throughout this book is self-similarity, which is dealt with in a second chapter with a particular emphasis on the celebrated Gaussian self-similar fields, called fractional Brownian fields after Mandelbrot and Van Ness''s seminal paper. Fundamental properties of fractional Brownian fields are then stated and proved. The second central notion of this book is the so-called local asymptotic self-similarity (in short lass), which is a local version of self-similarity, defined in the third chapter. A lengthy study is devoted to lass fields with finite variance. Among these lass fields, we find both Gaussian fields and non-Gaussian fields, called Lévy fields. The Lévy fields can be viewed as bridges between fractional Brownian fields and stable self-similar fields. A further key issue concerns the identification of fractional parameters. This is the raison d''être of the statistics chapter, where generalized quadratic variations methods are mainly used for estimating fractional parameters. Last but not least, the simulation is addressed in the last chapter. Unlike the previous issues, the simulation of fractional fields is still an area of ongoing research. The algorithms presented in this chapter are efficient but do not claim to close the debate.