Past exam of the mathematics course of the University of Cambridge 2013 iii Paper 7 4 Solution Created 2026-10-03 Updated 2026-10-14
We prove Kantorovich duality theorem here by a positive-functional extension argument; it produces the minimizing transport plan at the same time as equality of the values. Let and . This is a bounded continuous function because is a compact metric space. Write for the real space of continuous functions on a compact space, and letOn this vector subspace define . It is well-defined: two representations differ by a constant in the first variable and the opposite constant in the second, and both measures have mass one. It is positive, since implies and hence . Also .
Define the majorant envelope, which is a sublinear functional:Constants majorize every , and positivity gives , so this quantity is finite. Taking approximate minimizing majorants proves subadditivity; rescaling majorants proves positive homogeneity. Moreover for , and subtracting from a majorant provesThe dual value in the question is exactlySubadditivity at gives .
On , assign the value to . If the representation is unique. If , then , so the assignment is still well-defined. It is dominated by : for , use ; for , positive homogeneity gives . Together with the translation identity, these verify domination in both cases.
The real Hahn-Banach theorem extends this functional to with . If , then , so . Thus is a positive linear functional, with and . Positivity also gives , so is continuous. The Riesz-Markov-Kakutani representation theorem supplies a Borel probability measure on the compact space , satisfying .
For every , its pullback belongs to , so . Likewise . Uniqueness in the Riesz-Markov-Kakutani representation theorem shows that these are exactly the two marginal distributions. Finally, every feasible pair gives a lower bound for the cost of every transport plan, by integration. Our constructed plan achieves that bound:This Kantorovich duality by positive extension establishes the requested existence and equality without assuming an optimal plan in advance.
The metric structure additionally gives the Kantorovich–Rubinstein theorem formulation. For a feasible pair define . The triangle inequality for makes one-Lipschitz continuous, , and . Hence the dual objective is at most . Conversely is feasible for every one-Lipschitz . ThereforeNormalizing for a fixed gives a uniformly bounded equicontinuous family; it is closed and compact in the uniform topology by the Arzelà-Ascoli theorem. The objective is uniformly continuous on this family, so the supremum is attained as well. In particular, is the first Wasserstein distance between the two measures.
Past exam of the mathematics course of the University of Cambridge 2019 iii Paper 348 3 a Solution Created 2026-10-03 Updated 2026-10-05
The dual of the Kantorovich optimal transport problem iswhere the Kantorovich potentials are measurable representatives satisfyingOne standard form of the Kantorovich duality theorem assumes that are Polish spaces, are probability measures defined as Borel measures, and is sequentially lower semicontinuous. ThenThe primal infimum is attained; its value may be . Nonnegativity can be replaced by a constant lower bound by shifting the cost. This duality for lower semicontinuous costs is also discussed in Beiglboeck, Leonard and Schachermayer's duality paper.
Equality of values does not by itself assert a dual maximum. A sufficient stronger setting for attainment on both sides is compact metric spaces and a finite continuous cost ; then continuous Kantorovich potentials attain the dual supremum. The general statement above correctly uses a supremum.
Past exam of the mathematics course of the University of Cambridge 2019 iii Paper 348 3 b Solution Created 2026-10-03 Updated 2026-10-05
Fix any admissible pair of Kantorovich potentials and any transport plan . Its marginal distributions giveThe right side is well defined because and are Lebesgue integrable with respect to . Integrating their pointwise feasibility inequality givesSince this holds for every feasible pair and every transport plan,This proves the required inequality directly from the transport constraints, without any convex optimization duality theorem. Whenever the extrema are attained, the supremum and infimum can respectively be written as a maximum and minimum. Even the Kantorovich duality theorem is unnecessary for this direction.