Imaginary multiplicative chaos: Moments, regularity and connections to the Ising model

TL;DR

This paper explores the mathematical properties of imaginary Gaussian multiplicative chaos, its connections to the Ising model, and its potential as an analytical tool, providing both foundational theory and links to statistical physics models.

Contribution

It introduces and analyzes imaginary multiplicative chaos, establishing its properties and demonstrating its relevance to the critical planar Ising model and sine-Gordon field.

Findings

Imaginary chaos lives in specific distribution spaces.

Connections established between chaos and the Ising model.

Scaling limits relate to Gaussian free field and sine-Gordon field.

Abstract

In this article we study imaginary Gaussian multiplicative chaos -- namely a family of random generalized functions which can formally be written as $e^{i X(x)}$, where $X$ is a log-correlated real-valued Gaussian field on $\mathbb{R}^d$, i.e. it has a logarithmic singularity on the diagonal of its covariance. We study basic analytic properties of these random generalized functions, such as what spaces of distributions do these objects live in, along with their basic stochastic properties, such as moment and tail estimates. After this, we discuss connections between imaginary multiplicative chaos and the critical planar Ising model, namely that the scaling limit of the spin field of the so called critical planar XOR-Ising model can be expressed in terms of the cosine of the Gaussian free field, i.e. the real part of an imaginary multiplicative chaos distribution. Moreover, if one adds a magnetic perturbation to the XOR-Ising model, then the scaling limit of the spin field can be expressed in terms of the cosine of the sine-Gordon field, which can also be viewed as the real part of an imaginary multiplicative chaos distribution. The first sections of the article have been written in the style of a review, and we hope that the text will also serve as an introduction to imaginary chaos for an uninitiated reader.