AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home AIMS Mathematics Article
PDF (226.9 KB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Embedding reverse Carleson measure for derivatives on Fock space

Zhengyuan Zhuo1( ), Feifei Zhao2
School of Mathematics and Systems Science, Guangdong Polytechnic Normal University, Guangzhou, 510665, Guangdong, China
School of Liberal Arts and Sciences, North China Institute of Aerospace Engineering, Langfang, 065000, Hebei, China
Show Author Information

Abstract

The paper establishes a full characterisation of the embedding of Carleson measures and reverse Carleson measures for derivatives on Fock space. The intrinsic relationship between ( s , r )-averaging transform and embedding derivatives Carleson measures on Fock spaces is revealed. This improves existing results.

Keywords

reverse derivatives Carleson measureFock spaces
CLC number: Primary 47B37, 30H20

References

【1】
【1】
 
 
Crossref Google Scholar
AIMS Mathematics
Volume 11 Issue 5,
May 2026
Pages 14763-14770
DOI: 10.3934/math.2026607

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Cite this Report
Close
Close
Cite this article:
Zhuo Z, Zhao F. Embedding reverse Carleson measure for derivatives on Fock space. AIMS Mathematics, 2026, 11(5): 14763-14770. https://doi.org/10.3934/math.2026607

232

Views

2

Downloads

0

Crossref

0

Web of Science

0

Scopus
Received: 21 December 2025
Revised: 22 April 2026
Accepted: 21 May 2026
Published: 15 May 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)