Skip to main content
Birkhäuser
Book cover

From Lévy-Type Processes to Parabolic SPDEs

  • Textbook
  • © 2016

Overview

  • Studies invariance and comparison principles for parabolic SPDEs in a very general framework beyond the classical setting
  • Presents an extensive introduction to Lévy processes, including the different constructions
  • Provides properties of Feller processes as space inhomogeneous processes that behave locally like Lévy processes

Part of the book series: Advanced Courses in Mathematics - CRM Barcelona (ACMBIRK)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 29.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 39.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (19 chapters)

  1. Invariance and Comparison Principles for Parabolic Stochastic Partial Differential Equations

Keywords

About this book

This volume presents the lecture notes from two courses given by Davar Khoshnevisan and René Schilling, respectively, at the second Barcelona Summer School on Stochastic Analysis.

René Schilling’s notes are an expanded version of his course on Lévy and Lévy-type processes, the purpose of which is two-fold: on the one hand, the course presents in detail selected properties of the Lévy processes, mainly as Markov processes, and their different constructions, eventually leading to the celebrated Lévy-Itô decomposition. On the other, it identifies the infinitesimal generator of the Lévy process as a pseudo-differential operator whose symbol is the characteristic exponent of the process, making it possible to study the properties of Feller processes as space inhomogeneous processes that locally behave like Lévy processes. The presentation is self-contained, and includes dedicated chapters that review Markov processes, operator semigroups, random measures, etc.

Inturn, Davar Khoshnevisan’s course investigates selected problems in the field of stochastic partial differential equations of parabolic type. More precisely, the main objective is to establish an Invariance Principle for those equations in a rather general setting, and to deduce, as an application, comparison-type results. The framework in which these problems are addressed goes beyond the classical setting, in the sense that the driving noise is assumed to be a multiplicative space-time white noise on a group, and the underlying elliptic operator corresponds to a generator of a Lévy process on that group. This implies that stochastic integration with respect to the above noise, as well as the existence and uniqueness of a solution for the corresponding equation, become relevant in their own right. These aspects are also developed and supplemented by a wealth of illustrative examples.


Reviews

“The presentation also includes materials reviewing the classical theory of Markov processes, operator semigroups and random measures, which makes the notes self-contained and an excellent introductory material to the theory of  Lévy and Feller processes. ... It is nice to read and it provides exhaustive treatments of the topics.” (Nikola Sandrić, zbMATH 1382.60005, 2018)

Authors, Editors and Affiliations

  • Departament de Matemàtiques, Universitat Autònoma de Barcelona Departament de Matemàtiques, Bellaterra, Spain

    Frederic Utzet

  • Departament de Matematiques, Universitat Autonoma de Barcelona Departament de Matematiques, Bellaterra, Spain

    Lluis Quer-Sardanyons

  • Department of Mathematics, University of Utah, Salt Lake City, USA

    Davar Khoshnevisan

  • Institut für Mathematische Stochastik, Fachrichtung Mathematik TU Dresden, Dresden, Germany

    René Schilling

About the editors

Davar Khoshnevisan is Professor of Mathematics at The University of Utah.

René L. Schilling is Professor of Probability at Technische Universität Dresden.

Bibliographic Information

Publish with us