## Minimal Gaussian Partitions, Clustering Hardness and Voting (Steven Heilman, USC)

### October 29, 2018 @ 4:15 pm - 5:15 pm

A single soap bubble has a spherical shape since it minimizes its surface area subject to a fixed enclosed volume of air. When two soap bubbles collide, they form a “double-bubble” composed of three spherical caps. The double-bubble minimizes total surface area among all sets enclosing two fixed volumes. This was proven mathematically in a landmark result by Hutchings-Morgan-Ritore-Ros and Reichardt using the calculus of variations in the early 2000s. The analogous case of three or more Euclidean sets is considered difficult if not impossible. However, if we replace Lebesgue measure in these problems with the Gaussian measure, then recent work of myself (for 3 sets) and of Milman-Neeman (for any number of sets) can actually solve these problems. We also use the calculus of variations. We will discuss applications of this Gaussian “multi-bubble” problem to optimal clustering of data and to designing elections that are resilient to hacking.