Nonlocal basis pursuit: Nonlocal optimal design of conductive domains in the vanishing material limit
Anton Evgrafov, Jos\'e C. Bellido

TL;DR
This paper investigates the limiting behavior of nonlocal optimal design problems for conductive materials as the available material vanishes, revealing new solution spaces and a simplified approach to the local limit.
Contribution
It extends the understanding of nonlocal optimal design problems in the vanishing material limit, showing solutions in Lebesgue spaces and simplifying the transition to local problems by disregarding antisymmetry.
Findings
Nonlocal problems admit solutions in Lebesgue spaces with mixed exponents.
Disregarding antisymmetry transforms one-sided estimates into true limits.
The approach generalizes Sobolev space characterizations to mixed Lebesgue exponents.
Abstract
We consider the problem of optimal distribution of a limited amount of conductive material in systems governed by local and non-local scalar diffusion laws. Of particular interest for these problems is the study of the limiting case, which appears when the amount of available material is driven to zero. Such a limiting process is of both theoretical and practical interest and continues to be a subject of active study. In the local case, the limiting optimization problem is convex and has a well understood basis pursuit structure. Still this local problem is quite challenging both analytically and numerically because it is posed in the space of vector-valued Radon measures. With this in mind we focus on identifying the vanishing material limit for the corresponding nonlocal optimal design problem. Similarly to the local case, the resulting nonlocal problem is convex and has the basis…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNumerical methods in inverse problems · Nonlinear Partial Differential Equations · Numerical methods in engineering
