Can you hear the will of the People in the Vote? Quantifying Gerrymandering in NC using MCMC Sampling
Jonathan C. Mattingly
Barton Lectures in Computational Mathematics
Date: Wednesday, October 20, 2021
Time: 4:00 pm - 5:00 pm
Location: Virtual through Zoom
Jonathan C. Mattingly received a BS in Applied Mathematics with a concentration in physics from Yale University, and a PhD in Applied and Computational Mathematics in 1998 from Princeton. After 4 years as a Szego assistant professor at Stanford University and a year as a member of the Institute for Advanced Study in Princeton, he moved to Duke in 2003. His expertise is in the longtime behavior of stochastic systems including randomly forced fluid dynamics, turbulence, stochastic algorithms used in molecular dynamics and Bayesian sampling, and stochasticity in biochemical networks. Since 2013 he has also been working to understand and quantify gerrymandering and its interaction of a region's geopolitical landscape. This has led him to testify in a number of court cases including in North Carolina, which led to the NC congressional and both NC legislative maps being deemed unconstitutional and replaced for the 2020 elections. He is the recipient of a Sloan Fellowship and a PECASE CAREER award. He is also a fellow of the Institute for Mathematical Statistics and the American Mathematical Society. He was awarded the Defender of Freedom award by Common Cause for his work on Quantifying Gerrymandering.
The US political system is built on representatives chosen by geographically localized regions. This presents the government with the problem of designing these districts. The practice of harnessing this administrative process for partisan political gain is often referred to as gerrymandering. How does one identify and understand gerrymandering? Can we really recognize gerrymandering when we see it? If one party wins over 50% of the vote, is it fair that it wins less than 50% of the seats? What do we mean by fair? How can math help illuminate these questions? How does the geopolitical geometry of the state (where which groups live and the shape of the state) inform these answers? This is a story of interaction between lawyers, mathematicians, computational scientists and policy advocates. The problem of understanding gerrymandering has also prompted the development of a number of new computational algorithms which come with new mathematical questions.