## Seminar Categories

- Applied and Computational Math Colloquium (7)
- Applied and Computational Mathematics Seminar (1)
- Climate Seminar (26)
- Colloquium (7)
- Combinatorics Seminar (5)
- Commutative Algebra Seminar (5)
- Differential Geometry and Symplectic Topology Seminar (10)
- Dynamical Systems (1)
- IMA Data Science Lab Seminar (4)
- IMA/MCIM Industrial Problems Seminar (5)
- Math Biology Seminar (1)
- MCFAM Seminar (4)
- PDE Seminar (4)
- Probability Seminar (2)
- Special Events and Seminars (6)
- Student Number Theory Seminar (3)
- Topology Seminar (4)

## Current Series

Tue Oct 01 |
## Dynamical Systems2:30pm - Vincent Hall 209Relative equilibrium configurations of gravitationally interacting rigid bodies Rick Moeckel, University of Minnesota Consider a collection of n rigid, massive bodies interacting according to their mutual gravitational attraction. A relative equilibrium motion is one where the entire configuration rotates rigidly and uniformly about a fixed axis all of the bodies are phase locked. Such a motion is possible only for special positions and orientations of the bodies. A minimal energy motion is one which has the minimum possible energy in its fixed angular momentum level. While every minimal energy motion is a relative equilibrium motion, the main result here is that a relative equilibrium motion of n >= 3 disjoint rigid bodies is never an energy minimizer. Since energy minimizers are the expected final states produced by tidal interactions, phase locking of 3 or more bodies will not occur. |

Tue Oct 15 |
## Dynamical Systems2:30pm - Vincent Hall 209Forecasting U.S. elections with compartmental models of infection Alexandria Volkening, Northwestern University U.S. election forecasting involves polling likely voters, making assumptions about voter turnout, and accounting for various features such as state demographics and voting history. While political elections in the United States are decided at the state level, errors in forecasting are correlated between states. With the goal of shedding light on the forecasting process and exploring how states influence each other, we develop a framework for forecasting elections in the U.S. from the perspective of dynamical systems. Through a simple approach that borrows ideas from epidemiology, we show how to combine a compartmental model with public polling data from HuffPost and RealClearPolitics to forecast gubernatorial, senatorial, and presidential elections at the state level. Our results for the 2012 and 2016 U.S. races are largely in agreement with those of popular pollsters, and we use our new model to explore how subjective choices about uncertainty impact results. We conclude by comparing our forecasts for the senatorial and gubernatorial races in the U.S. midterm elections of 6 November 2018 with those of popular pollsters. This is joint work with Daniel Linder (Augusta Univ.), Mason Porter (UCLA), and Grzegorz Rempala (Ohio State Univ.) |

Fri Nov 15 |
## Dynamical Systems2:30pm - Vincent Hall 20The mathematics of taffy pulling Jean-Luc Thiffeault, University of Wisconsin Taffy is a type of candy made by repeated 'pulling' (stretching andfolding) a mass of heated sugar. The purpose of pulling is to get air |