Eigenvalue distribution of optimal transportation
classification
🧮 math.AP
math.FAmath.MG
keywords
measuresmathbbbrenierchoiceconcentrationconvexdimensiondistribution
read the original abstract
We investigate the Brenier map $\nabla \Phi$ between the uniform measures on two convex domains in $\mathbb{R}^n$ or more generally, between two log-concave probability measures on $\mathbb{R}^n$. We show that the eigenvalues of the Hessian matrix $D^2 \Phi$ exhibit remarkable concentration properties on a multiplicative scale, regardless of the choice of the two measures or the dimension $n$.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.