2020
DOI: 10.48550/arxiv.2010.10449
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Fourier restriction for smooth hyperbolic 2-surfaces

Abstract: We prove Fourier restriction estimates by means of the polynomial partitioning method for compact subsets of any sufficiently smooth hyperbolic hypersurface in R 3 . Our approach exploits in a crucial way the underlying hyperbolic geometry, which leads to a novel notion of strong transversality and corresponding "exceptional" sets. For the division of these exceptional sets we make crucial and perhaps surprising use of a lemma on level sets for sufficiently smooth one-variate functions from a previous article … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2022
2022

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 27 publications
0
1
0
Order By: Relevance
“…In particular, the operator does not seem to have a transverse equidistribution property, which is a key ingredient in [GOW + 21b]. Even though the restriction estimate for surfaces with negative Gaussian curvature is well understood in [GO20] and [BMV20], the arguments therein do not simply rely on the properties of wave packets. Thus, it is not straightforward to the authors whether their ideas can be applied to the operator E R f .…”
Section: Appendix: Approach Using Pseudo-conformal Transformationmentioning
confidence: 99%
“…In particular, the operator does not seem to have a transverse equidistribution property, which is a key ingredient in [GOW + 21b]. Even though the restriction estimate for surfaces with negative Gaussian curvature is well understood in [GO20] and [BMV20], the arguments therein do not simply rely on the properties of wave packets. Thus, it is not straightforward to the authors whether their ideas can be applied to the operator E R f .…”
Section: Appendix: Approach Using Pseudo-conformal Transformationmentioning
confidence: 99%