The gap between a variational problem and its occupation measure relaxation
Milan Korda, Rodolfo Rios-Zertuche

TL;DR
This paper investigates the relationship between classical variational problems and their occupation measure relaxations, proving equivalence in one-dimensional codomain cases and highlighting gaps in higher dimensions.
Contribution
It establishes conditions under which the minima of variational problems and their relaxations coincide, and provides counterexamples illustrating when gaps occur.
Findings
Classical and relaxed minima coincide when the codomain dimension is one.
Counterexample shows positive gaps can occur when both domain and codomain dimensions are greater than one.
Relaxed occupation measures can sometimes provide more conceptually satisfactory solutions.
Abstract
Recent works have proposed linear programming relaxations of variational optimization problems subject to nonlinear PDE constraints based on the occupation measure formalism. The main appeal of these methods is the fact that they rely on convex optimization, typically semidefinite programming. In this work we close an open question related to this approach. We prove that the classical and relaxed minima coincide when the dimension of the codomain of the unknown function equals one, both for calculus of variations and for optimal control problems, thereby complementing analogous results that existed for the case when the dimension of the domain equals one. In order to do so, we prove a generalization of the Hardt-Pitts decomposition of normal currents applicable in our setting. We also show by means of a counterexample that, if both the dimensions of the domain and of the codomain are…
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