Title: Multiscale inverse problem, from Schroedinger to Newton to Boltzmann

Speaker: Qin Li, Department of Mathematics

Date + Location: 7 March (Monday), Orchard View Room

Abstract: Inverse problems are ubiquitous. People probe the media with sources and measure the outputs. At the scale of quantum, classical, statistical and fluid, these are inverse Schroedinger, inverse Newton’s second law, inverse Boltzmann problem, and inverse diffusion respectively. The universe, however, should have a universal mathematical description, as Hilbert proposed in 1900. In this talk, we present a line of research results that unify all these inverse problems. Facing the IFDS crowd, I’d like to ask the following question: how to integrate the mathematical equivalence into the optimization formulation for a more efficient algorithmic pipeline than the traditional PDE-constrained optimization?

Bio: Qin Li is an associate professor of mathematics at UW-Madison. Her research lies between scientific computing and PDE-constrained optimization.