Discrete Applied Mathematics Seminar by Daryl DeFord: New Markov Chains for Sampling Connected Graph Partitions

Title: New Markov Chains for Sampling Connected Graph Partitions

Abstract: The problems of constructing “fair” political districts and detecting intentional gerrymandering have received a significant amount of attention in recent years. Attempting to analyze these issues from a computational perspective leads to a wide variety of interesting data-driven research problems in probability, graph theory, and geometry. In this talk, I will discuss recent work introducing Markov chains for sampling districting plans using spanning trees that addresses practical and theoretical questions in these fields. These techniques have also helped inform legislative reform efforts, support line-drawing commissions, and provide evidence in court challenges, including cases in the Supreme Court, and I will discuss what it is like to translate mathematical research to these applied settings, as well as some of the related data, computational, and communication challenges.

Discrete Applied Math Seminar