Gubinelli / Souganidis / Tzvetkov | Singular Random Dynamics | Buch | 978-3-030-29544-8 | sack.de

Buch, Englisch, Band 2253, 316 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 499 g

Reihe: Lecture Notes in Mathematics

Gubinelli / Souganidis / Tzvetkov

Singular Random Dynamics

Cetraro, Italy 2016
1. Auflage 2019
ISBN: 978-3-030-29544-8
Verlag: Springer International Publishing

Cetraro, Italy 2016

Buch, Englisch, Band 2253, 316 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 499 g

Reihe: Lecture Notes in Mathematics

ISBN: 978-3-030-29544-8
Verlag: Springer International Publishing


Written by leading experts in an emerging field, this book offers a unique view of the theory of stochastic partial differential equations, with lectures on the stationary KPZ equation, fully nonlinear SPDEs, and random data wave equations. This subject has recently attracted a great deal of attention, partly as a consequence of Martin Hairer's contributions and in particular his creation of a theory of regularity structures for SPDEs, for which he was awarded the Fields Medal in 2014.

The text comprises three lectures covering: the theory of stochastic Hamilton–Jacobi equations, one of the most intriguing and rich new chapters of this subject; singular SPDEs, which are at the cutting edge of innovation in the field following the breakthroughs of regularity structures and related theories, with the KPZ equation as a central example; and the study of dispersive equations with random initial conditions, which gives new insights into classical problems and at the same timeprovides a surprising parallel to the theory of singular SPDEs, viewed from many different perspectives.

These notes are aimed at graduate students and researchers who want to familiarize themselves with this new field, which lies at the interface between analysis and probability.


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Weitere Infos & Material


- Introduction. - Lectures on Energy Solutions for the Stationary KPZ Equation. - Pathwise Solutions for Fully Nonlinear First- and Second-Order Partial Differential Equations with Multiplicative Rough Time Dependence. - Random Data Wave Equations.



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