| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4589751 | Journal of Functional Analysis | 2016 | 38 Pages |
Abstract
We propose a new definition of the Gaussian multiplicative chaos and an approach based on the relation of subcritical Gaussian multiplicative chaos to randomized shifts of a Gaussian measure. Using this relation we prove general results on uniqueness and convergence for subcritical Gaussian multiplicative chaos that hold for Gaussian fields with arbitrary covariance kernels.
Related Topics
Physical Sciences and Engineering
Mathematics
Algebra and Number Theory
Authors
Alexander Shamov,