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PreprintCC0arXiv

Sharp helical maximal estimates in all dimensions

Abstract

We establish sharp Lp maximal estimates for averages over smooth nondegenerate curves in ℝn for p>n. More precisely, we show that for any nondegenerate curve γ in ℝn and the associated maximal operator M f(x):=supt>0 |∫−11f(x−tγ(s))χ(s) ds|, the estimate | Mf|Lp(ℝn)≲γ,p,n |f|Lp(ℝn) holds for all p>n. A new ingredient is a weighted Kakeya-type estimate.

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BibTeX
@misc{gan2026sharp,
  title = {{Sharp helical maximal estimates in all dimensions}},
  author = {Shengwen Gan and Changkeun Oh and Jaehoon Shin},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.37250},
  eprint = {2610.37250},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.37250},
  note = {CC0},
}
RIS
TY  - UNPB
TI  - Sharp helical maximal estimates in all dimensions
AU  - Shengwen Gan
AU  - Changkeun Oh
AU  - Jaehoon Shin
PY  - 2026
DA  - 2026/10/27
PB  - arXiv
DO  - 10.48550/arxiv.2610.37250
UR  - https://arxiv.org/abs/2610.37250
AB  - We establish sharp L^p maximal estimates for averages over smooth nondegenerate curves in ℝ^n for p>n. More precisely, we show that for any nondegenerate curve γ in ℝ^n and the associated maximal operator M f(x):=sup_t>0 |∫_−1^1f(x−tγ(s))χ(s) ds|, the estimate | Mf|_L^p(ℝ^n)≲_γ,p,n |f|_L^p(ℝ^n) holds for all p>n. A new ingredient is a weighted Kakeya-type estimate.
ER  -