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

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arxiv 1806.02118 v2 pith:LQNQ7HZL submitted 2018-06-06 math.PR math-phmath.MP

classification math.PRmath-phmath.MP
keywords chaosimaginaryfieldmultiplicativemodelgaussianarticlebasic
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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.

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  1. Brownian Loops, Layering Fields and Imaginary Gaussian Multiplicative Chaos

    math.PR 2019-08 accept novelty 7.0 of 10

    Renormalized Brownian loop soup layering fields converge in an appropriate Sobolev sense to a tilted imaginary Gaussian multiplicative chaos with covariance kernel given by the Brownian loop measure.

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