When does the norm of a Fourier multiplier dominate its L∞ norm?

Alexei Karlovich, Eugene Shargorodsky

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

One can define Fourier multipliers on a Banach function space using the direct and inverse Fourier transforms on L2(ℝn) or using the direct Fourier transform on S(ℝn) and the inverse one on S(ℝn). In the former case, one assumes that the Fourier multipliers belong to L(ℝn), while in the latter one this requirement may or may not be included in the definition. We provide sufficient conditions for those definitions to coincide as well as examples when they differ. In particular, we prove that if a Banach function space X(ℝn) satisfies a certain weak doubling property, then the space of all Fourier multipliers Mx(ℝn) is continuously embedded into L(ℝn) with the best possible embedding constant one. For weighted Lebesgue spaces Lp(ℝn, w), the weak doubling property is much weaker than the requirement that w is a Muckenhoupt weight, and our result implies that (Formula presented.) for such weights. This inequality extends the inequality for n=1 from Theorem of [Berkson and Gillespie, Bull. Sci. Math. 122 (1998) 427–454], where it is attributed to J. Bourgain. We show that although the weak doubling property is not necessary, it is quite sharp. It allows the weight w in Lp(ℝn, w) to grow at any subexponential rate. On the other hand, the space L,p(ℝex has plenty of unbounded Fourier multipliers.

Original languageEnglish
JournalProceedings of the London Mathematical Society
DOIs
Publication statusAccepted/In press - 2018

Fingerprint Dive into the research topics of 'When does the norm of a Fourier multiplier dominate its L∞ norm?'. Together they form a unique fingerprint.

Cite this