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PreprintarXiv licencearXiv

Sharp endpoint extension inequalities for the moment curve on finite fields II: an extremal property of the uniform distribution

Abstract

We identify the optimal constant and describe all maximizers for the Fourier endpoint extension inequality associated with the moment curve over finite fields. This confirms a conjecture proposed in the authors' earlier work. The proof proceeds by showing that the problem is equivalent to a purely probabilistic extremal statement: among all probability distributions on a finite set, the uniform distribution uniquely maximizes the expected number of distinct rearrangements of an i.i.d. sample.

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BibTeX
@misc{biswas2026sharp,
  title = {{Sharp endpoint extension inequalities for the moment curve on finite fields II: an extremal property of the uniform distribution}},
  author = {Chandan Biswas and Emanuel Carneiro and Taryn C. Flock and José Madrid and Diogo Oliveira e Silva and Betsy Stovall and James Tautges},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.29882},
  eprint = {2609.29882},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.29882},
}
RIS
TY  - UNPB
TI  - Sharp endpoint extension inequalities for the moment curve on finite fields II: an extremal property of the uniform distribution
AU  - Chandan Biswas
AU  - Emanuel Carneiro
AU  - Taryn C. Flock
AU  - José Madrid
AU  - Diogo Oliveira e Silva
AU  - Betsy Stovall
AU  - James Tautges
PY  - 2026
DA  - 2026/09/24
PB  - arXiv
DO  - 10.48550/arxiv.2609.29882
UR  - https://arxiv.org/abs/2609.29882
AB  - We identify the optimal constant and describe all maximizers for the Fourier endpoint extension inequality associated with the moment curve over finite fields. This confirms a conjecture proposed in the authors' earlier work. The proof proceeds by showing that the problem is equivalent to a purely probabilistic extremal statement: among all probability distributions on a finite set, the uniform distribution uniquely maximizes the expected number of distinct rearrangements of an i.i.d. sample.
ER  -