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Constrained steepest descent in the 2-Wasserstein metric. (English) Zbl 1038.49040
Summary: We study several constrained variational problems in the 2-Wasserstein metric for which the set of probability densities satisfying the constraint is not closed. For example, given a probability density \(F_0\) on \(\mathbb{R}^d\) and a time-step \(h>0\), we seek to minimize \(I(F)=hS(F)+ W_2^2(F_0,F)\) over all of the probability densities \(F\) that have the same mean and variance as \(F_0\), where \(S(F)\) is the entropy of \(F\). We prove existence of minimizers. We also analyze the induced geometry of the set of densities satisfying the constraint on the variance and means, and we determine all of the geodesics on it. From this, we determine a criterion for convexity of functionals in the induced geometry. It turns out, for example, that the entropy is uniformly strictly convex on the constrained manifold, though not uniformly convex without the constraint. The problems solved here arose in a study of a variational approach to constructing and studying solutions of the nonlinear kinetic Fokker-Planck equation, which is briefly described here and fully developed in a companion paper.

MSC:
49Q20 Variational problems in a geometric measure-theoretic setting
35Q99 Partial differential equations of mathematical physics and other areas of application
60H15 Stochastic partial differential equations (aspects of stochastic analysis)
49J10 Existence theories for free problems in two or more independent variables
82C31 Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics
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