A generalization of Caffarelli’s contraction theorem via (reverse) heat flow
By Young-Heon Kim, Emanuel Milman. Mathematische Annalen, 2010
69 citations recorded by the source corpus.
A theorem of L. Caffarelli implies the existence of a map, pushing forward a source Gaussian measure to a target measure which is more log-concave than the source one, which contracts Euclidean distance (in fact, Caffarelli showed that the optimal-transport Brenier map Topt is a contraction in this case). We generalize this result to more general source and target measures, using a condition on the third derivative of the potential, by providing two different proofs. The first uses a map T, whose inverse is constructed as a flow along an advection field associated to an appropriate heat-diffusion process. The contraction property is then reduced to showing that log-concavity is preserved along the corresponding diffusion semi-group, by using a maximum principle for parabolic PDE. In particular, Caffarelli’s original result immediately follows by using the Ornstein–Uhlenbeck process and the Prékopa–Leindler Theorem. The second uses the map Topt by generalizing Caffarelli’s argument, employing in addition further results of Caffarelli. As applications, we obtain new correlation and isoperimetric inequalities.
Subfields: Applied Mathematics
View Paper: https://www.semanticscholar.org/paper/65cf532074f5a5f34b381774782d27b276661063
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In Applied Mathematics
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Citations in the corpus
- Log-Concavity and Strong Log-Concavity: a review (2014, background): “See also Caffarelli (1991), Caffarelli (1992), Caffarelli (2000), and Kim and Milman (2012) for results on (strongly) log-concave measures.”
- Stochastic Interpolants: A Unifying Framework for Flows and Diffusions (2023, background): “Moreover, the dynamics of these stochastic processes also emit a probability flow equation at the level of the distribution, first noted [2, 35, 23] and then applied in [32, 40, 24, 4].”