Stochastic Partial Differential Equations

This course provides a basic introduction into the theory of stochastic differential equations in infinite dimensions and stochastic PDEs. Topics include Gaussian measures on Hilbert spaces, Brownian motion and stochastic integrals in infinite dimensions, and Hilbert space-valued SDEs and their connections to SPDEs.    

The lecture takes place 

  • Mondays, 9-11, Room 1.114 (RUD 25)

The tutorials take place

  • Mondays, 11-13, Room 1.114 (RUD 25)

The first part of the course will be taught by U. Horst; the second part will be taught by G. Fu. 

Prerequisites: 

  • Stochastic II 
  • Functional Analysis
  • basic knowledge of Stochastic Calculus (Brownian motion, path-wise Ito Calculus) 
  • specific knowledge of PDE theory is not required

We will mostly follow the book A Concise Course on Stochastic Partial Differential Equations by C. Prevot and M. Röckner. The book is available online for HU students. For the necessary functional analysis background we recommend the very nice book on functional analysis book by Reed & Simon. 

Some exercises