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We establish the limiting distribution of $\frac{{(\log \log x)}^{1/4}}{\sqrt{x}} \sum_{n\le x}\alpha(n)$ where $\alpha$ is a Steinhaus random multiplicative function, answering a question of Harper. The distributional convergence is proved…

Number Theory · Mathematics 2025-09-16 Ofir Gorodetsky , Mo Dick Wong

Let $\alpha$ be a Steinhaus random multiplicative function. For a wide class of multiplicative functions $f$ we construct a multiplicative chaos measure arising from the Dirichlet series of $\alpha f$, in the whole $L^1$-regime. Our method…

Number Theory · Mathematics 2025-09-16 Ofir Gorodetsky , Mo Dick Wong

Gaussian Multiplicative Chaos (GMC) is informally defined as a random measure $e^{\gamma X} \mathrm{d} x$ where $X$ is Gaussian field on $\mathbb R^d$ (or an open subset of it) whose correlation function is of the form $ K(x,y)= \log…

Probability · Mathematics 2020-12-23 Hubert Lacoin

We study how the Gaussian multiplicative chaos (GMC) measures $\mu^\gamma$ corresponding to the 2D Gaussian free field change when $\gamma$ approaches the critical parameter $2$. In particular, we show that as $\gamma\to 2^{-}$,…

Probability · Mathematics 2020-04-14 Juhan Aru , Ellen Powell , Avelio Sepúlveda

We present a simple criterion, only based on second moment assumptions, for the convergence of polynomial or Wiener chaos to a Gaussian limit. We exploit this criterion to obtain new Gaussian asymptotics for the partition functions of…

Probability · Mathematics 2022-10-07 Francesco Caravenna , Francesca Cottini

In this article, we consider the multiplicative chaos measure associated to the log-correlated random Fourier series, or random wave model, with i.i.d. coefficients taken from a general class of distributions. This measure was shown to be…

Probability · Mathematics 2025-12-17 Yujin H. Kim , Xaver Kriechbaum

We present new, short and self-contained proofs of the convergence (with an adequate renormalization) of four different sequences to the critical Gaussian Multiplicative Chaos:(a) the derivative martingale (b) the critical martingale (c)…

Probability · Mathematics 2022-09-15 Hubert Lacoin

In this article, we study complex Gaussian multiplicative chaos. More precisely, we study the renormalization theory and the limit of the exponential of a complex log-correlated Gaussian field in all dimensions (including Gaussian Free…

Probability · Mathematics 2015-02-17 Hubert Lacoin , Rémi Rhodes , Vincent Vargas

In this paper, we establish the exact Fourier dimensions of all standard sub-critical Gaussian multiplicative chaos on the unit interval, thereby confirming the Garban-Vargas conjecture. The proof relies on a significant improvement of the…

Probability · Mathematics 2025-05-07 Zhaofeng Lin , Yanqi Qiu , Mingjie Tan

In this article we systematically study the general properties and the single-point moments of the inverse of the Gaussian multiplicative chaos.

Probability · Mathematics 2024-05-30 Ilia Binder , Tomas Kojar

We study one-dimensional exact scaling lognormal multiplicative chaos measures at criticality. Our main results are the determination of the exact asymptotics of the right tail of the distribution of the total mass of the measure, and an…

Probability · Mathematics 2015-10-28 Julien Barral , Antti Kupiainen , Miika Nikula , Eero Saksman , Christian Webb

We study the total mass of high points in a random model for the Riemann-Zeta function. We consider the same model as in [8], [2], and build on the convergence to 'Gaussian' multiplicative chaos proved in [14]. We show that the total mass…

Probability · Mathematics 2019-06-24 Louis-Pierre Arguin , Lisa Hartung , Nicola Kistler

We prove that multiplicative chaos measures can be constructed from extreme level sets or thick points of the underlying logarithmically correlated field. We develop a method which covers the whole subcritical phase and only requires…

Probability · Mathematics 2023-03-22 Janne Junnila , Gaultier Lambert , Christian Webb

We study the characteristic polynomial of Haar distributed random unitary matrices. We show that after a suitable normalization, as one increases the size of the matrix, powers of the absolute value of the characteristic polynomial as well…

Probability · Mathematics 2015-10-05 Christian Webb

Gaussian multiplicative chaos (GMC) is a canonical random fractal measure obtained by exponentiating log-correlated Gaussian processes, first constructed in the seminal work of Kahane (1985). Since then it has served as an important…

Probability · Mathematics 2025-02-25 Mriganka Basu Roy Chowdhury , Shirshendu Ganguly

We study the characteristic polynomials of both the Gaussian Orthogonal and Symplectic Ensembles. We show that for both ensembles, powers of the absolute value of the characteristic polynomials converge in law to Gaussian multiplicative…

Probability · Mathematics 2022-10-28 Pax Kivimae

We construct and study properties of an infinite dimensional analog of Kahane's theory of Gaussian multiplicative chaos \cite{K85}. Namely, if $H_T(\omega)$ is a random field defined w.r.t. space-time white noise $\dot B$ and integrated…

Probability · Mathematics 2025-07-09 Rodrigo Bazaes , Isabel Lammers , Chiranjib Mukherjee

We consider a sub-critical Gaussian multiplicative chaos (GMC) measure defined on the unit interval [0,1] and prove an exact formula for the fractional moments of the total mass of this measure. Our formula includes the case where…

Probability · Mathematics 2019-11-06 Guillaume Remy , Tunan Zhu

In the paper [25], written in collaboration with Gesine Reinert, we proved a universality principle for the Gaussian Wiener chaos. In the present work, we aim at providing an original example of application of this principle in the…

Probability · Mathematics 2010-02-08 Ivan Nourdin , Giovanni Peccati

Denote by $\mu_\beta="\exp(\beta X)"$ the Gaussian multiplicative chaos which is defined using a log-correlated Gaussian field $X$ on a domain $U\subset\mathbb{R}^d$. The case $\beta\in\mathbb{R}$ has been studied quite intensively, and…

Probability · Mathematics 2019-05-30 Janne Junnila , Eero Saksman , Lauri Viitasaari