Nonlinear Fokker-Planck flows and their probabilistic counterparts

• Verfasst von: Barbu, Viorel [VerfasserIn]
• Verfasst von: Röckner, Michael [VerfasserIn]
• Titel: Nonlinear Fokker-Planck flows and their probabilistic counterparts
• Institutionen: Springer Nature Switzerland AG [Verlag]
• Verf.angabe: Viorel Barbu, Michael Röckner
• Verlagsort: Cham, Switzerland
• Verlag: Springer
• E-Jahr: 2024
• Jahr: [2024]
• Umfang: ix, 212 Seiten
• Format: 23,5 cm
• Gesamttitel/Reihe: Lecture notes in mathematics ; volume 2353
• Fussnoten: Literaturverzeichnis: Seite 205-209
• ISBN: 978-3-031-61733-1
• Schlagwörter: (s)Fokker-Planck-Gleichung / (s)Langzeitverhalten / (s)Lösung <Mathematik> / (s)McKean-Vlasov-Prozess
• Schlagwörter: (s)Nichtlinearer Prozess / (s)Markov-Prozess / (s)Stochastische Differentialgleichung
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Online-Ausgabe: Barbu, Viorel, 1941 - : Nonlinear Fokker-Planck Flows and their Probabilistic Counterparts. - 1st ed. 2024.. - Cham : Springer Nature Switzerland, 2024. - 1 Online-Ressource(IX, 214 p.)
• K10plus-PPN: 1894705203

Abstract

This book delves into a rigorous mathematical exploration of the well-posedness and long-time behavior of weak solutions to nonlinear Fokker-Planck equations, along with their implications in the theory of probabilistically weak solutions to McKean-Vlasov stochastic differential equations and the corresponding nonlinear Markov processes. These are widely acknowledged as essential tools for describing the dynamics of complex systems in disordered media, as well as mean-field models. The resulting stochastic processes elucidate the microscopic dynamics underlying the nonlinear Fokker-Planck equations, whereas the solutions of the latter describe the evolving macroscopic probability distributions. The intended audience for this book primarily comprises specialists in mathematical physics, probability theory and PDEs. It can also be utilized as a one-semester graduate course for mathematicians. Prerequisites for the readers include a solid foundation in functional analysis and probability theory.