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This paper analyzes the limit properties of the empirical process of $\alpha$-stable random variables with long range dependence. The $\alpha$-stable random variables are constructed by non-linear transformations of bivariate sequences of…

Statistics Theory · Mathematics 2015-07-29 Emanuele Taufer

We discuss in a stochastic framework the interplay between Riemann-Liouville type operators applied to stochastic processes, real interpolation, bounded mean oscillation, and an approximation problem for stochastic integrals. We provide…

Probability · Mathematics 2021-08-24 Stefan Geiss , Tran-Thuan Nguyen

In this second paper on loop quantization of Gowdy model, we introduce the kinematical Hilbert space on which appropriate holonomies and fluxes are well represented. The quantization of the volume operator and the Gauss constraint is…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Kinjal Banerjee , Ghanashyam Date

The non-parametric estimation of covariance lies at the heart of functional data analysis, whether for curve or surface-valued data. The case of a two-dimensional domain poses both statistical and computational challenges, which are…

Statistics Theory · Mathematics 2022-01-19 Tomas Masak , Soham Sarkar , Victor M. Panaretos

We study one-dimensional spin-1/2 models in which strict confinement of Ising domain walls leads to the fragmentation of Hilbert space into exponentially many disconnected subspaces. Whereas most previous works emphasize dipole moment…

Strongly Correlated Electrons · Physics 2020-05-26 Zhi-Cheng Yang , Fangli Liu , Alexey V. Gorshkov , Thomas Iadecola

Let $\{X_{1}(t)\}_{0\leq t\leq1}$ and $\{X_{2}(t)\}_{0\leq t\leq1}$ be two independent continuous centered Gaussian processes with covariance functions$R_{1}$ and $R_{2}$. This paper shows that if the covariance functions are of finite…

Probability · Mathematics 2010-07-16 Albert Ferreiro-Castilla , Frederic Utzet

The aim of this paper is to investigate, which infinite dimensional consequences follow from the main results of recently published paper of the authors (2009) (see Theorems 2 and 3). We show that the finite dimensional Theorem 3 implies…

Probability · Mathematics 2012-03-27 Friedrich Götze , Andrei Yu. Zaitsev

Many time-dependent linear partial differential equations of mathematical physics and continuum mechanics can be phrased in the form of an abstract evolutionary system defined on a Hilbert space. In this paper we discuss a general framework…

Analysis of PDEs · Mathematics 2019-05-09 Stefan Neukamm , Mario Varga , Marcus Waurick

In this article a unified approach to iterative soft-thresholding algorithms for the solution of linear operator equations in infinite dimensional Hilbert spaces is presented. We formulate the algorithm in the framework of generalized…

Functional Analysis · Mathematics 2010-10-26 Kristian Bredies , Dirk A. Lorenz

In this work we study the unitary time-evolutions of quantum systems defined on infinite-dimensional separable time-dependent Hilbert spaces. Two possible cases are considered: a quantum system defined on a stochastic interval and another…

Quantum Physics · Physics 2019-05-22 Luca Curcuraci , Stefano Bacchi , Angelo Bassi

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

In this work, we establish conditions ensuring convergence in distribution of a sequence admitting a Wiener-It\^o chaos representation to a nondegenerate Gaussian measure on a separable Hilbert space. Our first main result shows that,…

Probability · Mathematics 2025-12-02 Marie-Christine Düker , Pavlos Zoubouloglou

The paper proves several limit theorems for linear eigenvalue statistics of overlapping Wigner and sample covariance matrices. It is shown that the covariance of the limiting multivariate Gaussian distribution is diagonalized by choosing…

Probability · Mathematics 2015-11-10 Vladislav Kargin

We provide a detailed description of the model Hilbert space $L^2(\bbR; d\Sigma; \cK)$, were $\cK$ represents a complex, separable Hilbert space, and $\Sigma$ denotes a bounded operator-valued measure. In particular, we show that several…

Spectral Theory · Mathematics 2011-11-04 Fritz Gesztesy , Rudi Weikard , Maxim Zinchenko

The assumption of separability of the covariance operator for a random image or hypersurface can be of substantial use in applications, especially in situations where the accurate estimation of the full covariance structure is unfeasible,…

Methodology · Statistics 2017-06-29 John A. D. Aston , Davide Pigoli , Shahin Tavakoli

We consider estimation of a sparse parameter vector that determines the covariance matrix of a Gaussian random vector via a sparse expansion into known "basis matrices". Using the theory of reproducing kernel Hilbert spaces, we derive lower…

Information Theory · Computer Science 2011-01-21 Alexander Jung , Sebastian Schmutzhard , Franz Hlawatsch , Alfred O. Hero

A discrete gradient model for interfaces is studied. The interaction potential is a non-convex perturbation of the quadratic gradient potential. Based on a representation for the finite volume Gibbs measure obtained via a renormalization…

Mathematical Physics · Physics 2016-03-16 Susanne Hilger

We study the phenomenon of Hilbert space fragmentation in isolated Hamiltonian and Floquet quantum systems using the language of commutant algebras, the algebra of all operators that commute with each term of the Hamiltonian or each gate of…

Statistical Mechanics · Physics 2022-03-29 Sanjay Moudgalya , Olexei I. Motrunich

This note deals with a problem of the probabilistic Ramsey theory in functional analysis. Given a linear operator $T$ on a Hilbert space with an orthogonal basis, we define the isomorphic structure $\Sigma(T)$ as the family of all subsets…

Functional Analysis · Mathematics 2016-12-23 Roman Vershynin

We provide lower error bounds for randomized algorithms that approximate integrals of functions depending on an unrestricted or even infinite number of variables. More precisely, we consider the infinite-dimensional integration problem on…

Numerical Analysis · Mathematics 2021-02-09 Michael Gnewuch