Calculus of Variations and Geometric Measure Theory

A. Arroyo-Rabasa

Relaxation and optimization for linear-growth convex integral functionals under PDE constraints

created by arroyorabasa on 07 Feb 2017
modified on 21 Aug 2019


Accepted Paper

Inserted: 7 feb 2017
Last Updated: 21 aug 2019

Journal: Journal of Functional Analysis
Year: 2016


We give necessary and sufficient conditions for minimality of generalized minimizers for linear-growth functionals of the form \[ \mathcal F[u] = \int_\Omega f(x,u(x)) \, \text{d}x, \quad u: \Omega \subset \mathbb R^d \to \mathbb R^N \] where u is an integrable function satisfying a general PDE constraint. Our analysis is based on two ideas: a relaxation argument into a subspace of the space of bounded vector-valued Radon measures $\mathcal M(\Omega;\mathbb R^N)$, and the introduction of a set-valued pairing in $\mathcal M(Ω;\mathbb R^N) \times {\rm L}^\infty(\Omega;\mathbb R^N)$. By these means we are able to show an intrinsic relation between minimizers of the relaxed problem and maximizers of its dual formulation also known as the saddle-point conditions. In particular, our results can be applied to relaxation and minimization problems in ${\rm BV, BD}$.

Keywords: relaxation, optimality condition, functional on measures, linear growth