Directional oscillations, concentrations, and compensated compactness via microlocal compactness forms
Filip Rindler

TL;DR
This paper introduces microlocal compactness forms (MCFs), a new analytical tool that captures detailed oscillation and concentration behaviors in sequences of functions, extending existing theories like Young measures and H-measures.
Contribution
The paper develops the theory of MCFs, enabling precise analysis of oscillations, concentrations, and differential constraints, with applications to compensated compactness and PDE singularities.
Findings
MCFs extend Young measures and H-measures by including directional and location information.
A new weak-to-strong compactness theorem is established using MCFs.
Applications include analysis of microstructures, anisotropic functionals, and PDE singularities.
Abstract
This work introduces microlocal compactness forms (MCFs) as a new tool to study oscillations and concentrations in -bounded sequences of functions. Decisively, MCFs retain information about the location, value distribution, and direction of oscillations and concentrations, thus extending at the same time the theories of (generalized) Young measures and H-measures. In -spaces oscillations and concentrations precisely discriminate between weak and strong compactness, and thus MCFs allow to quantify the difference in compactness. The definition of MCFs involves a Fourier variable, whereby also differential constraints on the functions in the sequence can be investigated easily - a distinct advantage over Young measure theory. Furthermore, pointwise restrictions are reflected in the MCF as well, paving the way for applications to Tartar's framework of compensated…
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 Mathematical Modeling in Engineering · Stability and Controllability of Differential Equations · Numerical methods in inverse problems
