A local proof for the characterization of Young measures generated by sequences in BV
Filip Rindler

TL;DR
This paper provides a new, localized proof for the characterization of Young measures generated by BV sequences, utilizing advanced localization and Hahn-Banach techniques, and introduces homogeneous Young measures at different points.
Contribution
It offers a novel proof avoiding relaxation theorems, introduces homogeneous Young measures at regular and singular points, and demonstrates how to generate sequences respecting atomic parts.
Findings
New proof technique based on localization and Hahn-Banach
Introduction of homogeneous Young measures at different points
Ability to generate sequences respecting atomic parts in BV-Young measures
Abstract
This work presents a new proof of the recent characterization theorem for generalized Young measures generated by sequences in BV by Kristensen and the author [Arch. Ration. Mech. Anal. 197 (2010), 539-598]. The present argument is based on a localization technique together with a local Hahn-Banach argument in novel function spaces combined with an application of Alberti's Rank-One Theorem. This strategy avoids employing a relaxation theorem as in the previously known proof, and the new tools introduced in its course should prove useful in other contexts as well. In particular, we introduce homogeneous Young measures, separately at regular and singular points, which exhibit rather different behaviour than the classical homogeneous Young measures. As an application, we show how for BV-Young measures with an atomic part one can find a generating sequence respecting this structure.
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
TopicsAdvanced Banach Space Theory · Approximation Theory and Sequence Spaces · Advanced Mathematical Modeling in Engineering
