Optimal Coffee shops, Numerical Integration and Kantorovich-Rubinstein duality

Speaker
Stefan Steinerberger, University of Washington (Math)
Date
2021-01-30 10:00 AM PST
Event
PIHOT kick-off event
Location
Online (zoom)
Registration
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Abstract

Suppose you want to open up 7 coffee shops so that people in the downtown area have to walk the least amount to get their morning coffee.
That’s a classical problem in Optimal Transport, minimizing the Wasserstein distance between the sum of 7 Dirac measures and the (coffee-drinking) population density. But in reality things are trickier. If the 7 coffee shops go well, you want to open an 8th and a 9th and you want to remain optimal in this respect (and the first 7 are already fixed). We find optimal rates for this problem in $W_2$ in all dimensions. Analytic Number Theory makes an appearance and, in fact, Optimal Transport can tell us something new about $\sqrt{2}$. All of this is also related to the question of approximating an integral by sampling in a number of points and a conjectured extension of the Kantorovich-Rubinstein duality regarding the $W_1$ distance and testing of two measures against Lipschitz functions.