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The spectral properties of a set of local gauge-invariant composite operators are investigated in the $U(1)$ Higgs model quantized in the 't Hooft $R_{\xi}$ gauge. These operators enable us to give a gauge-invariant description of the…

The Friedman's urn model is a popular urn model which is widely used in many disciplines. In particular, it is extensively used in treatment allocation schemes in clinical trials. In this paper, we prove that both the urn composition…

Probability · Mathematics 2009-08-30 Li-Xin Zhang , Feifang Hu

Bayesian learning using Gaussian processes provides a foundational framework for making decisions in a manner that balances what is known with what could be learned by gathering data. In this dissertation, we develop techniques for…

Machine Learning · Statistics 2022-04-29 Alexander Terenin

Surrogate modeling based on Gaussian processes (GPs) has received increasing attention in the analysis of complex problems in science and engineering. Despite extensive studies on GP modeling, the developments for functional inputs are…

Methodology · Statistics 2023-01-04 Chih-Li Sung , Wenjia Wang , Fioralba Cakoni , Isaac Harris , Ying Hung

We present a new framework for recycling independent variational approximations to Gaussian processes. The main contribution is the construction of variational ensembles given a dictionary of fitted Gaussian processes without revisiting any…

Machine Learning · Statistics 2020-10-07 Pablo Moreno-Muñoz , Antonio Artés-Rodríguez , Mauricio A. Álvarez

This paper discusses a general method for spectral type theorems using metric spaces instead of vector spaces. Advantages of this approach are that it applies to genuinely non-linear situations and also to random versions. Metric analogs of…

Metric Geometry · Mathematics 2019-04-03 Anders Karlsson

We consider the accuracy of an approximate posterior distribution in nonparametric regression problems by combining posterior distributions computed on subsets of the data defined by the locations of the independent variables. We show that…

Statistics Theory · Mathematics 2025-04-29 Botond Szabo , Amine Hadji , Aad van der Vaart

In this paper, we investigate the testing problem that the spectral density matrices of several, not necessarily independent, stationary processes are equal. Based on an $L_2$-type test statistic, we propose a new nonparametric approach,…

Statistics Theory · Mathematics 2015-06-03 Carsten Jentsch , Markus Pauly

Recently, the spectral geometric mean has been studied by some papers. In this paper, we firstly estimate the H\"{o}lder type inequality of the spectral geometric mean of positive invertible operators on the Hilbert space for all real order…

Functional Analysis · Mathematics 2024-12-17 Shigeru Furuichi , Yuki Seo

Iterates of quantum operations and their convergence are investigated in the context of mean ergodic theory. We discuss in detail the convergence of the iterates and show that the uniform ergodic theorem plays an essential role. Our results…

Mathematical Physics · Physics 2022-06-14 J. Z. Bernád

We collect and summarize results on the unitary equivalence of Gabor systems by pairs of unitary operators and global isometries. The methods are then used to study Gabor systems with Hermite functions. We provide new proofs of some known…

Functional Analysis · Mathematics 2025-02-17 Markus Faulhuber

As of 2005, sampling has been incorporated in all major database systems. While efficient sampling techniques are realizable, determining the accuracy of an estimate obtained from the sample is still an unresolved problem. In this paper, we…

Databases · Computer Science 2013-07-02 Supriya Nirkhiwale , Alin Dobra , Chris Jermaine

We show that the unitary operator on a separable Hilbert space is a parametrization of any conditional probability measure in a standard measure space. We propose unitary inference, a generalization of Bayesian inference. We study…

General Physics · Physics 2023-10-13 Leonardo Pedro

We present a spectral analysis for matrix scaling and operator scaling. We prove that if the input matrix or operator has a spectral gap, then a natural gradient flow has linear convergence. This implies that a simple gradient descent…

Data Structures and Algorithms · Computer Science 2019-04-09 Tsz Chiu Kwok , Lap Chi Lau , Akshay Ramachandran

Consider an infinite-dimensional linear space equipped with a Gaussian measure and the group $GL(\infty)$ of linear transformations that send the measure to equivalent one. Limit points of $GL(\infty)$ can be regarded as 'spreading' maps…

Representation Theory · Mathematics 2012-11-27 Yury A. Neretin

We study essentially bounded quantum random variables and show that the Gelfand spectrum of such a quantum random variable coincides with the hypoconvex hull of its essential range. Moreover, a notion of operator-valued variance is…

Quantum Physics · Physics 2015-10-07 Douglas Farenick , Michael J. Kozdron , Sarah Plosker

The extraction of spectral densities from Euclidean correlators evaluated on the lattice is an important problem, as these quantities encode physical information on scattering amplitudes, finite-volume spectra, inclusive decay rates, and…

High Energy Physics - Lattice · Physics 2023-12-01 Luigi Del Debbio , Alessandro Lupo , Marco Panero , Nazario Tantalo

The mathematical description of the quantum harmonic oscillator is essentially based on the Gaussian function. In the case of a quantum oscillator with finite-dimensional Hilbert space, the position space consists in a finite number of…

Mathematical Physics · Physics 2015-12-09 Nicolae Cotfas

Two types of Gaussian processes, namely the Gaussian field with generalized Cauchy covariance (GFGCC) and the Gaussian sheet with generalized Cauchy covariance (GSGCC) are considered. Some of the basic properties and the asymptotic…

Probability · Mathematics 2010-07-28 S. C. Lim , L. P. Teo

New results on uniform convergence in probability for the most general classes of wavelet expansions of stationary Gaussian random processes are given.

Probability · Mathematics 2013-07-10 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak