Date: June 27-July 11, 2022
Organizers: Jacob Bedrossian, Jessica Lin and Jean-Christophe Mourrat
In order to make deeper and more practical connections to physical problems, many branches of the theory of partial differential equations (PDEs) have started to introduce random components in their models. This includes the study of PDEs in random environments (stochastic homogenization), the analysis of PDEs with randomized initial data, and the introduction of stochastic forcing terms. Such problems incorporate various aspects of probability and analysis. The purpose of this workshop is to bring together a diversity of experts, postdocs, and students working in these different branches in order to compare perspectives and exchange ideas, techniques, and intuitions entering the analysis of these problems. As the title suggests, the ultimate goal is to identify unifying concepts within the study of PDEs with randomness.
The workshop will include short courses given by Scott Armstrong, Jonathan Mattingly, Pierre-Emmanuel Jabin and Vlad Vicol.