An introduction to extended Gevrey regularity
Nenad Teofanov, Filip Tomi\'c, Milica \v{Z}igi\'c

TL;DR
This paper provides an overview of extended Gevrey regularity, a framework for analyzing smooth functions with weaker regularity than traditional Gevrey classes, including dual spaces, microlocal analysis, and applications.
Contribution
It offers a comprehensive survey of extended Gevrey classes, clarifies their key features, and discusses related dual spaces, microlocal analysis, and potential applications.
Findings
Extended Gevrey classes encompass functions with weaker regularity than Gevrey functions.
The paper reviews dual spaces of ultradistributions in the context of extended Gevrey regularity.
Applications suggest new directions for research in regularity theory and microlocal analysis.
Abstract
Gevrey classes are the most common choice when considering the regularities of smooth functions that are not analytic. However, in various situations, it is important to consider smoothness properties that go beyond Gevrey regularity, for example when initial value problems are ill-posed in Gevrey settings. Extended Gevrey classes provide a convenient framework for studying smooth functions that possess weaker regularity than any Gevrey function. Since the available literature on this topic is scattered, our aim is to provide an overview to extended Gevrey regularity, highlighting its most important features. Additionally, we consider related dual spaces of ultradistributions and review some results on micro-local analysis in the context of extended Gevrey regularity. We conclude the paper with a few selected applications that may motivate further study of the topic.
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 · Advanced Numerical Methods in Computational Mathematics
