A variational proof of a disentanglement theorem for multilinear norm inequalities

Anthony Carbery, Timo S. Hänninen, Stefán Ingi Valdimarsson

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The basic disentanglement theorem established by the present authors states that estimates on a weighted geometric mean over (convex) families of functions can be disentangled into quantitatively linked estimates on each family separately. On the one hand, the theorem gives a uniform approach to classical results including Maurey's factorisation theorem and Lozanovskiĭ's factorisation theorem, and, on the other hand, it underpins the duality theory for multilinear norm inequalities developed in our previous two papers. In this paper we give a simple proof of this basic disentanglement theorem. Whereas the approach of our previous paper was rather involved – it relied on the use of minimax theory together with weak*-compactness arguments in the space of finitely additive measures, and an application of the Yosida–Hewitt theory of such measures – the alternate approach of this paper is rather straightforward: it instead depends upon elementary perturbation and compactness arguments.
Original languageEnglish
Article number110460
JournalJournal of Functional Analysis
Volume287
Issue number2
Number of pages21
ISSN0022-1236
DOIs
Publication statusPublished - 2024
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 111 Mathematics

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