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arxiv: 1507.04187 · v1 · pith:XR3YGLIAnew · submitted 2015-07-15 · 🧮 math.FA · math.AP

Dealing with moment measures via entropy and optimal transport

classification 🧮 math.FA math.AP
keywords measurestransportcharacterizationconvexcorrespondingentropyfunctionsmethod
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A recent paper by Cordero-Erausquin and Klartag provides a characterization of the measures $\mu$ on $\R^d$ which can be expressed as the moment measures of suitable convex functions $u$, i.e. are of the form $(\nabla u)\_\\#e^{- u}$ for $u:\R^d\to\R\cup\{+\infty\}$ and finds the corresponding $u$ by a variational method in the class of convex functions. Here we propose a purely optimal-transport-based method to retrieve the same result. The variational problem becomes the minimization of an entropy and a transport cost among densities $\rho$ and the optimizer $\rho$ turns out to be $e^{-u}$. This requires to develop some estimates and some semicontinuity results for the corresponding functionals which are natural in optimal transport. The notion of displacement convexity plays a crucial role in the characterization and uniqueness of the minimizers.

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