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Related papers: Simulation of Gaussian random field in a ball

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This article presents a neural network approach for estimating the covariance function of spatial Gaussian random fields defined in a portion of the Euclidean plane. Our proposal builds upon recent contributions, expanding from the purely…

Methodology · Statistics 2024-08-21 Alejandro Villazón , Alfredo Alegría , Xavier Emery

The efficient simulation of isotropic Gaussian random fields on the unit sphere is a task encountered frequently in numerical applications. A fast algorithm based on Markov properties and fast Fourier Transforms in 1d is presented that…

Numerical Analysis · Mathematics 2018-04-16 Peter E. Creasey , Annika Lang

Series expansions of isotropic Gaussian random fields on $\mathbb{S}^2$ with independent Gaussian coefficients and localized basis functions are constructed. Such representations with multilevel localised structure provide an alternative to…

Probability · Mathematics 2022-06-27 Markus Bachmayr , Ana Djurdjevac

The problem of constructing flexible stochastic models to describe the variability in shape of solid particles is challenging. Natural objects often exhibit mono- or multi-fractal features, i.e. irregular shapes and self-similar patterns.…

Statistics Theory · Mathematics 2019-01-24 Alfredo Alegría

Motivated by the modeling of the spatial structure of the velocity field of three-dimensional turbulent flows, and the phenomenology of cascade phenomena, a linear dynamics has been recently proposed able to generate high velocity gradients…

We develop variational regularization methods which leverage sparsity-promoting priors to solve severely ill posed inverse problems defined on the 3D ball (i.e. the solid sphere). Our method solves the problem natively on the ball and thus…

Information Theory · Computer Science 2021-05-13 Matthew A. Price , Jason D. McEwen

We are concerned with the fast simulation of random fields on closed surfaces in $\mathbb{R}^3$ which are generated by the (Whittle-) Mat\'ern class of covariance functions. To this end, we solve the underlying fractional stochastic partial…

Numerical Analysis · Mathematics 2026-05-26 Helmut Harbrecht , Florian Sonderegger , Remo von Rickenbach

We study the peak height distribution of certain non-stationary Gaussian random fields. The explicit peak height distribution of smooth, non-stationary Gaussian processes in 1D with general covariance is derived. The formula is determined…

Methodology · Statistics 2025-02-19 Yu Zhao , Dan Cheng , Samuel Davenport , Armin Schwartzman

In this article, we consider a configuration of weighted random balls in $\mathbb{R}^d$ generated according to a Poisson point process. The model investigated exhibits inhomogeneity, as well as dependence between the centers and the radii…

Probability · Mathematics 2014-06-04 Renan Gobard

We obtain formulae for the expected number and height distribution of critical points of smooth isotropic Gaussian random fields parameterized on Euclidean space or spheres of arbitrary dimension. The results hold in general in the sense…

Probability · Mathematics 2016-09-20 Dan Cheng , Armin Schwartzman

The paper deals with multivariate Gaussian random fields defined over generalized product spaces that involve the hypertorus. The assumption of Gaussianity implies the finite dimensional distributions to be completely specified by the…

Statistics Theory · Mathematics 2022-02-23 François Bachoc , Ana Peron , Emilio Porcu

Generating large-scale samples of stationary random fields is of great importance in the fields such as geomaterial modeling and uncertainty quantification. Traditional methodologies based on covariance matrix decomposition have the…

Methodology · Statistics 2022-08-23 Bin Zhu , Jiahao Liu , Zhengshou Lai , Tao Qian

We discuss recent results of the replica approach to statistical mechanics of a single classical particle placed in a random N(>>1)-dimensional Gaussian landscape. The particular attention is paid to the case of landscapes with…

Disordered Systems and Neural Networks · Physics 2008-01-07 Yan V Fyodorov

This paper describes the generation of initial conditions for numerical simulations in cosmology with multiple levels of resolution, or multiscale simulations. We present the theory of adaptive mesh refinement of Gaussian random fields…

Astrophysics · Physics 2009-07-09 Edmund Bertschinger

In this work, we study probability functions associated with Gaussian mixture models. Our primary focus is on extending the use of spherical radial decomposition for multivariate Gaussian random vectors to the context of Gaussian mixture…

Optimization and Control · Mathematics 2024-11-06 Gonzalo Contador , Pedro Pérez-Aros , Emilio Vilches

This paper introduces a generalised 3rd-order Spectral Representation Method for the simulation of multi-dimensional stochastic fields with asymmetric non-linearities. The simulated random fields satisfy a prescribed Power Spectrum and…

Statistics Theory · Mathematics 2020-07-06 Lohit Vandanapu , Michael D. Shields

Gaussian Schell-model fields are examples of spatially partially coherent fields, which in recent years have found several unique applications. The existing techniques for generating Gaussian Schell-model (GSM) fields are based on…

Optics · Physics 2019-10-01 Abhinandan Bhattacharjee , Rishabh Sahu , Anand K. Jha

We introduce a simple representation for isotropic spherical random fields and we discuss how it allows to discuss different notions of sparsity under isotropy. We also show how a suitable construction of sparse fields can mimic well the…

Probability · Mathematics 2026-01-30 Giacomo Greco , Domenico Marinucci

We address a detailed non-perturbative numerical study of the scalar theory on the fuzzy sphere. We use a novel algorithm which strongly reduces the correlation problems in the matrix update process, and allows the investigation of…

High Energy Physics - Theory · Physics 2010-10-27 Marco Panero

For a vector random field that is isotropic and mean square continuous on a sphere and stationary on a temporal domain, this paper derives a general form of its covariance matrix function and provides a series representation for the random…

Probability · Mathematics 2016-04-26 Chunsheng Ma