The decomposition of optimal transportation problems with convex cost

preprint2014arXivOpen access

Abstract

Given a positive l.s.c. convex function c:Rd→Rd\mathtt c : \mathbb R^d \to \mathbb R^d and an optimal transference plane π‾\underlineπ for the transportation problem \begin{equation*} \int \mathtt c(x'-x) π(dxdx'), \end{equation*} we show how the results of \cite{biadan} on the existence of a \emph{Sudakov decomposition} for norm cost c=∣⋅∣\mathtt c= |\cdot| can be extended to this case. More precisely, we prove that there exists a partition of Rd\mathbb R^d into a family of disjoint sets {Sah}h,a\{S^h_\mathfrak a\}_{h,\mathfrak a} together with the projection {Oah}h,a\{O^h_\mathfrak a\}_{h,\mathfrak a} on Rd\mathbb R^d of proper extremal faces of epi c\mathrm{epi}\, \mathtt c, h=0,…,dh = 0,\dots,d and a∈Ah⊂Rd−h\mathfrak a \in \mathfrak A^h \subset \mathbb R^{d-h}, such that - SahS^h_\mathfrak a is relatively open in its affine span, and has affine dimension hh; \item OahO^h_\mathfrak a has affine dimension hh and is parallel to SahS^h_\mathfrak a; - Ld(Rd∖∪h,aSah)=0\mathcal L^d(\mathbb R^d \setminus \cup_{h,\mathfrak a} S^h_\mathfrak a) = 0, and the disintegration of Ld\mathcal L^d, Ld=∑h∫ξahηh(da)\mathcal L^d = \sum_h \int ξ^h_\mathfrak a η^h(d\mathfrak a), w.r.t. SahS^h_\mathfrak a has conditional probabilities ξah≪Hh⌞Sahξ^h_\mathfrak a \ll \mathcal H^h \llcorner_{S^h_\mathfrak a}; - the sets SahS^h_\mathfrak a are essentially cyclically connected and cannot be further decomposed. \end{list} The last point is used to prove the existence of an optimal transport map. The main idea is to recast the problem in (t,x)∈[0,∞]×Rd(t,x) \in [0,\infty] \times \mathbb R^d with an 11-homogeneous norm cˉ(t,x):=tc(−xt)\bar{\mathtt c}(t,x) := t \mathtt c(- \frac{x}{t}) and to extend the regularity estimates of \cite{biadan} to this case.

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