English
Related papers

Related papers: Stein-Malliavin Approximations for Nonlinear Funct…

200 papers

We prove Central Limit Theorems and Stein-like bounds for the asymptotic behaviour of nonlinear functionals of spherical Gaussian eigenfunctions. Our investigation combine asymptotic analysis of higher order moments for Legendre polynomials…

Mathematical Physics · Physics 2015-06-11 Domenico Marinucci , Igor Wigman

In this short survey we recollect some of the recent results on the high energy behavior (i.e., for diverging sequences of eigenvalues) of nonlinear functionals of Gaussian eigenfunctions on the $d$-dimensional sphere $\mathbb S^d$, $d\ge…

Probability · Mathematics 2015-06-08 Maurizia Rossi

Random hyperspherical harmonics are Gaussian Laplace eigenfunctions on the unit $d$-dimensional sphere ($d\ge 2$). We study the convergence in Total Variation distance for their nonlinear statistics in the high energy limit, i.e., for…

Probability · Mathematics 2023-11-14 Lucia Caramellino , Giacomo Giorgio , Maurizia Rossi

A lot of efforts have been devoted in the last decade to the investigation of the high-frequency behaviour of geometric functionals for the excursion sets of random spherical harmonics, i.e., Gaussian eigenfunctions for the spherical…

Probability · Mathematics 2021-12-10 Domenico Marinucci

We consider Gaussian random waves on hyperbolic spaces and establish variance asymptotics and central limit theorems for a large class of their integral functionals, both in the high-frequency and large domain limits. Our strategy of proof…

Probability · Mathematics 2023-02-14 Francesco Grotto , Giovanni Peccati

We consider large non-Hermitian random matrices $X$ with complex, independent, identically distributed centred entries and show that the linear statistics of their eigenvalues are asymptotically Gaussian for test functions having…

Probability · Mathematics 2023-10-16 Giorgio Cipolloni , László Erdős , Dominik Schröder

We show how to detect optimal Berry--Esseen bounds in the normal approximation of functionals of Gaussian fields. Our techniques are based on a combination of Malliavin calculus, Stein's method and the method of moments and cumulants, and…

Probability · Mathematics 2009-12-09 Ivan Nourdin , Giovanni Peccati

We propose the notion of $E_{2}$-quasi-exact solvability and apply this idea to find explicit solutions to the eigenvalue problem for a non-Hermitian Hamiltonian system depending on two parameters. The model considered reduces to the…

Quantum Physics · Physics 2015-05-18 Andreas Fring

Stein's method is a method of probability approximation which hinges on the solution of a functional equation. For normal approximation the functional equation is a first order differential equation. Malliavin calculus is an…

Probability · Mathematics 2015-05-11 Louis H. Y. Chen

We establish the convergence of the densities of a sequence of nonlinear functionals of an underlying Gaussian process to the density of a Gamma distribution. The key idea of our work is a new density formula for random variables in the…

Probability · Mathematics 2025-11-17 Solesne Bourguin , Thanh Dang , Yaozhong Hu

We introduce a framework to derive quantitative central limit theorems in the context of non-linear approximation of Gaussian random variables taking values in a separable Hilbert space. In particular, our method provides an alternative to…

Probability · Mathematics 2020-11-25 Solesne Bourguin , Simon Campese

We develop techniques for determining the exact asymptotic speed of convergence in the multidimensional normal approximation of smooth functions of Gaussian fields. As a by-product, our findings yield exact limits and often give rise to…

Probability · Mathematics 2015-10-09 Simon Campese

We establish central and non-central limit theorems for sequences of functionals of the Gaussian output of an infinitely-wide random neural network on the d-dimensional sphere . We show that the asymptotic behaviour of these functionals as…

Probability · Mathematics 2026-04-24 Simmaco Di Lillo , Leonardo Maini , Domenico Marinucci

Random hyperspherical harmonics are Gaussian Laplace eigenfunctions on the unit $d$-sphere ($d\ge 2$). We investigate the distribution of their defect i.e., the difference between the measure of positive and negative regions. Marinucci and…

Probability · Mathematics 2018-07-24 Maurizia Rossi

Analysis of non-compact manifolds almost always requires some controlled behavior at infinity. Without such, one neither can show, nor expect, strong properties. On the other hand, such assumptions restrict the possible applications and…

Differential Geometry · Mathematics 2021-09-13 Tobias Holck Colding , William P. Minicozzi

In this paper, we establish explicit quantitative Berry-Esseen bounds in the hyper-rectangle distance $d_R$, the convex distance $d_{\mathscr{C}}$ and the $1$-Wasserstein distance $d_W$ for high-dimensional, non-linear functionals of…

Probability · Mathematics 2026-02-03 Andreas Basse-O'Connor , David Kramer-Bang

We combine Malliavin calculus with Stein's method, in order to derive explicit bounds in the Gaussian and Gamma approximations of random variables in a fixed Wiener chaos of a general Gaussian process. We also prove results concerning…

Probability · Mathematics 2008-05-10 Ivan Nourdin , Giovanni Peccati

We show how it is possible to assess the rate of convergence in the Gaussian approximation of triangular arrays of $U$-statistics, built from wavelets coefficients evaluated on a homogeneous spherical Poisson field of arbitrary dimension.…

Probability · Mathematics 2017-12-20 Solesne Bourguin , Claudio Durastanti , Domenico Marinucci , Giovanni Peccati

The electronic Schr\"odinger equation describes the motion of N electrons under Coulomb interaction forces in a field of clamped nuclei. The solutions of this equation, the electronic wavefunctions, depend on 3N variables, three spatial…

Numerical Analysis · Mathematics 2017-01-16 Stephan Scholz , Harry Yserentant

We consider estimating the parametric components of semi-parametric multiple index models in a high-dimensional and non-Gaussian setting. Such models form a rich class of non-linear models with applications to signal processing, machine…

Statistics Theory · Mathematics 2018-07-19 Zhuoran Yang , Krishnakumar Balasubramanian , Han Liu
‹ Prev 1 2 3 10 Next ›