Time parallel time integration methods for multiscale systems, with application in uncertainty quantification and optimization

Time parallel methods iteratively refine a cheap but inaccurate time integration by computing a sequence of corrections on different portions of the time domain in parallel. Such methods promise extra opportunities for parallellisation on exascale high performance computing architectures. In this PhD, we will study time parallel time integration methods for multiscale systems and apply them in the context of uncertainty quantification and optimization, integrating the time parallellisation iterations within the optimization loop.