A GAUSSIAN VERSION OF LITTLEWOOD'S THEOREM FOR RANDOM POWER SERIES

Guozheng Cheng, Xiang Fang, Kunyu Guo, Chao Liu

Research output: Contribution to journalArticlepeer-review

Abstract

We prove a Littlewood-type theorem for random analytic functions associated with not necessarily independent Gaussian processes. We show that if we randomize a function in the Hardy space H2(D) by a Gaussian process whose covariance matrix K induces a bounded operator on l2, then the resulting random function is almost surely in Hp(D) for any p > 0. The case K = Id, the identity operator, recovers Littlewood's theorem. A new ingredient in our proof is to recast the membership problem as the boundedness of an operator. This reformulation enables us to use tools in functional analysis and is applicable to other situations.

Original languageEnglish
Pages (from-to)3525-3536
Number of pages12
JournalProceedings of the American Mathematical Society
Volume150
Issue number8
DOIs
StatePublished - 1 Aug 2022

Keywords

  • covariance matrix
  • Gaussian process
  • Hardy space
  • Random analytic function

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