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Related papers: Derivatives of Gaussian multiplicative chaos

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We present several refinements on the fluctuations of sequences of random vectors (with values in the Euclidean space $\mathbb{R}^d$) which converge after normalization to a multidimensional Gaussian distribution. More precisely we refine…

Probability · Mathematics 2022-03-04 Pierre-Loïc Méliot , Ashkan Nikeghbali

The moving average of the complex modulus of the analytic wavelet transform provides a robust time-scale representation for signals to small time shifts and deformation. In this work, we derive the Wiener chaos expansion of this…

Probability · Mathematics 2024-10-23 Gi-Ren Liu , Yuan-Chung Sheu , Hau-Tieng Wu

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

We consider real, Gauss-divisible matrices $A_{t}=A+\sqrt{t}B$, where $B$ is from the real Ginibre ensemble. We prove that the bulk correlation functions converge to a universal limit for $t=O(N^{-1/3+\epsilon})$ if $A$ satisfies certain…

Probability · Mathematics 2024-09-30 Mohammed Osman

We prove a bound for the Wasserstein distance between vectors of smooth complex random variables and complex Gaussians in the framework of complex Markov diffusion generators. For the special case of chaotic eigenfunctions, this bound can…

Probability · Mathematics 2015-11-03 Simon Campese

In a recent paper the author obtained optimal bounds for the strong Gaussian approximation of sums of independent $\R^d$-valued random vectors with finite exponential moments. The results may be considered as generalizations of well-known…

Probability · Mathematics 2007-05-23 A. Yu. Zaitsev

A new method for approximating fractional derivatives of the Gaussian function and Dawson's integral are presented. Unlike previous approaches, which are dominantly based on some discretization of Riemann-Liouville integral using polynomial…

Numerical Analysis · Mathematics 2017-09-08 Can Evren Yarman

We study the regularity of the law of a quadratic form $Q(X,X)$, evaluated in a sequence $X = (X_{i})$ of independent and identically distributed random variables, when $X_{1}$ can be expressed as a sufficiently smooth function of a…

Probability · Mathematics 2024-06-21 Ronan Herry , Dominique Malicet , Guillaume Poly

The gravitational evolution of the cosmic one-point probability distribution function (PDF) has been estimated using an analytic approximation that combines gravitational perturbation theory with the Edgeworth expansion around a Gaussian…

Astrophysics · Physics 2009-10-31 E. Gaztanaga , P. Fosalba , E. Elizalde

In this note we continue the study of imaginary multiplicative chaos $\mu_\beta := \exp(i \beta \Gamma)$, where $\Gamma$ is a two-dimensional continuum Gaussian free field. We concentrate here on the fine-scale analytic properties of…

Probability · Mathematics 2025-01-17 Juhan Aru , Guillaume Baverez , Antoine Jego , Janne Junnila

Time-independent Hamiltonian flows are viewed as geodesic flows in a curved manifold, so that the onset of chaos hinges on properties of the curvature two-form entering into the Jacobi equation. Attention focuses on ensembles of orbit…

Astrophysics · Physics 2009-10-30 Henry E. Kandrup

Let $h$ be a log-correlated Gaussian field on $\R^d$, let $\gamma \in (0,\sqrt{2d}),$ let $\mu_h$ be the $\gamma$-Gaussian multiplicative chaos measure, and let $D_h$ be an exponential metric associated with $h$ satisfying certain natural…

Probability · Mathematics 2024-10-18 Andres A. Contreras Hip , Ewain Gwynne

We consider the random field defined by the layering numbers of the Brownian loop soup in a bounded simply connected domain in the complex plane. We call this the layering field and show that, after a suitable renormalization, it converges…

Probability · Mathematics 2025-10-28 Sayantan Maitra

This paper presents the Gaussian subordination framework to generate optimal one-sided approximations to multidimensional real-valued functions by functions of prescribed exponential type. Such extremal problems date back to the works of…

Classical Analysis and ODEs · Mathematics 2021-09-30 Emanuel Carneiro , Friedrich Littmann

Matrix square roots and their inverses arise frequently in machine learning, e.g., when sampling from high-dimensional Gaussians $\mathcal{N}(\mathbf 0, \mathbf K)$ or whitening a vector $\mathbf b$ against covariance matrix $\mathbf K$.…

Machine Learning · Computer Science 2020-12-02 Geoff Pleiss , Martin Jankowiak , David Eriksson , Anil Damle , Jacob R. Gardner

We investigate the low moments $\mathbb{E}[|A_N|^{2q}], 0<q\leq 1$ of {secular coefficients} $A_N$ of the {critical non-Gaussian holomorphic multiplicative chaos}, i.e. coefficients of $z^N$ in the power series expansion of…

Probability · Mathematics 2025-06-18 Haotian Gu , Zhenyuan Zhang

We combine Malliavin calculus with Stein's method to derive bounds for the Variance-Gamma approximation of functionals of isonormal Gaussian processes, in particular of random variables living inside a fixed Wiener chaos induced by such a…

Probability · Mathematics 2014-09-22 Peter Eichelsbacher , Christoph Thäle

We quantify the large deviations of Gaussian extreme value statistics on closed convex sets in d-dimensional Euclidean space. The asymptotics imply that the extreme value distribution exhibits a rate function that is a simple quadratic…

Probability · Mathematics 2018-10-31 Harsha Honnappa , Raghu Pasupathy , Prateek Jaiswal

We study the evolution of matter density perturbations in Galileon cosmology where the late-time cosmic acceleration can be realized by a field kinetic energy. We obtain full perturbation equations at linear order in the presence of five…

Cosmology and Nongalactic Astrophysics · Physics 2011-02-23 Antonio De Felice , Ryotaro Kase , Shinji Tsujikawa

We examine several characteristics of conformal maps that resemble the variance of a Gaussian: asymptotic variance, the constant in Makarov's law of iterated logarithm and the second derivative of the integral means spectrum at the origin.…

Complex Variables · Mathematics 2016-04-20 Oleg Ivrii
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