Generalized sign Fourier uncertainty
Emanuel Carneiro, Emily Quesada-Herrera

TL;DR
This paper explores a generalized sign uncertainty principle for the Fourier transform, analyzing how functions and their transforms resonate with a given pattern outside a certain region, and identifies sharp constants in some cases.
Contribution
It extends the sign uncertainty principle to a broader setting involving a generic function P, providing new sharp constants and insights into the resonance behavior.
Findings
Identified sharp constants for the generalized sign uncertainty principle.
Extended the classical uncertainty principle to a more general framework involving a function P.
Provided conditions under which resonance can occur outside a specified region.
Abstract
We consider a generalized version of the sign uncertainty principle for the Fourier transform, first proposed by Bourgain, Clozel and Kahane in 2010 and revisited by Cohn and Gon\c{c}alves in 2019. In our setup, the signs of a function and its Fourier transform resonate with a generic given function outside of a ball. One essentially wants to know if and how soon this resonance can happen, when facing a suitable competing weighted integral condition. The original version of the problem corresponds to the case . Surprisingly, even in such a rough setup, we are able to identify sharp constants in some cases.
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
TopicsMedical Imaging Techniques and Applications · Model Reduction and Neural Networks · Mathematical Analysis and Transform Methods
