PreprintCC BY 4.0arXiv
Sharp weighted estimates for the multilinear maximal operator
Abstract
The paper contains the study of the weighted Lp1× Lp2× … × Lpm→ Lp estimates for the multilinear maximal operator, in the context of abstract probability spaces equipped with a tree-like structure. Using the Bellman function method, we identify the associated optimal constants for weights satisfying the multilinear Muckenhoupt condition.
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BibTeX
@misc{galazka2026sharp,
title = {{Sharp weighted estimates for the multilinear maximal operator}},
author = {Tomasz Gałązka and Yong Jiao and Adam Osękowski and Lian Wu},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.09515},
eprint = {2610.09515},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.09515},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Sharp weighted estimates for the multilinear maximal operator
AU - Tomasz Gałązka
AU - Yong Jiao
AU - Adam Osękowski
AU - Lian Wu
PY - 2026
DA - 2026/10/07
PB - arXiv
DO - 10.48550/arxiv.2610.09515
UR - https://arxiv.org/abs/2610.09515
AB - The paper contains the study of the weighted L^p_1× L^p_2× … × L^p_m→ L^p estimates for the multilinear maximal operator, in the context of abstract probability spaces equipped with a tree-like structure. Using the Bellman function method, we identify the associated optimal constants for weights satisfying the multilinear Muckenhoupt condition.
ER -