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Spartan Spatial Random Fields (SSRFs) are generalized Gibbs random fields, equipped with a coarse-graining kernel that acts as a low-pass filter for the fluctuations. SSRFs are defined by means of physically motivated spatial interactions…

Information Theory · Computer Science 2012-04-12 Dionissios T. Hristopulos , Samuel Elogne

This paper studies Gaussian random fields with Mat\'ern covariance functions with smooth parameter $\nu>2$. Two cases of parameter spaces, the Euclidean space and $N$-dimensional sphere, are considered. For such smooth Gaussian fields, we…

Probability · Mathematics 2024-03-27 Dan Cheng

This paper investigates aliasing effects emerging from the reconstruction from discrete samples of spin spherical random fields defined on the two-dimensional sphere. We determine the location in the frequency domain and the intensity of…

Probability · Mathematics 2026-01-26 Claudio Durastanti

Two universal predictions of general relativity are the propagation of gravitational waves of large momentum along null geodesics and the isospectrality of quasinormal modes in many families of black holes. In extensions of general…

High Energy Physics - Theory · Physics 2024-07-30 Pablo A. Cano , Marina David

Spatial stochastic processes that are modeled over the entire Earth's surface require statistical approaches that directly consider the spherical domain. Here, we extend the notion of intrinsic random functions (IRF) to model non-stationary…

Statistics Theory · Mathematics 2016-06-08 Chunfeng Huang , Haimeng Zhang , Scott M. Robeson , Jacob Shields

Gaussian random fields (GRFs) constitute an important part of spatial modelling, but can be computationally infeasible for general covariance structures. An efficient approach is to specify GRFs via stochastic partial differential equations…

Methodology · Statistics 2016-08-11 Geir-Arne Fuglstad , Finn Lindgren , Daniel Simpson , Håvard Rue

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

As the hunt for an Earth-like exoplanets has intensified in recent years, so has the effort to characterise and model the stellar signals that can hide or mimic small planetary signals. Stellar variability arises from a number of sources,…

Solar and Stellar Astrophysics · Physics 2024-04-19 Niamh K. O'Sullivan , Suzanne Aigrain

We review the Dudley integral for the Belyaev dichotomy applied to Gaussian processes on spheres, and discuss the approximate (or restricted) continuity of paths in the discontinuous case. We discuss also the spatio-temporal case, of sphere…

Probability · Mathematics 2019-08-21 N. H. Bingham , Tasmin L. Symons

Covariance representations are developed for the uniform distributions on the Euclidean spheres in terms of spherical gradients and Hessians. They are applied to derive a number of Sobolev type inequalities and to recover and refine the…

Probability · Mathematics 2024-03-29 Sergey G. Bobkov , Devraj Duggal

The angular power spectrum of a stationary random field on the sphere is estimated from the needlet coefficients of a single realization, observed with increasingly fine resolution. The estimator we consider is similar to the one recently…

Statistics Theory · Mathematics 2008-07-15 Gilles Faÿ , Frédéric Guilloux

We consider the propagation of flexural waves across a nearly flat, thin membrane, whose stress-free state is curved. The stress-free configuration is specified by a quenched height field, whose Fourier components are drawn from a Gaussian…

Soft Condensed Matter · Physics 2021-05-19 Jonathan Kernes , Alex J. Levine

An initially homogeneous freely evolving fluid of inelastic hard spheres develops inhomogeneities in the flow field (vortices) and in the density field (clusters), driven by unstable fluctuations. Their spatial correlations, as measured in…

Statistical Mechanics · Physics 2009-10-30 J. A. G. Orza , R. Brito , T. P. C. Van Noije , M. H. Ernst

We give a review of the theory of random fields defined on the observable part of the Universe that satisfy the cosmological principle, i.e., invariant with respect to the 6-dimensional group $\mathcal{G}$ of the isometries of the time…

Probability · Mathematics 2016-03-07 Anatoliy Malyarenko

We expand on a recent determination of the first global energy spectrum of the ocean's surface geostrophic circulation (Storer et al., 2022) using a coarse-graining (CG) method. We compare spectra from CG to those from spherical harmonics…

Atmospheric and Oceanic Physics · Physics 2023-07-12 Michele Buzzicotti , Benjamin A. Storer , Hemant Khatri , Stephen M. Griffies , Hussein Aluie

Obtaining constraints from the largest scales of a galaxy survey is challenging due to the survey mask allowing only partial measurement of large angular modes. This scatters information from the harmonic-space 2-point function away from…

Cosmology and Nongalactic Astrophysics · Physics 2022-02-16 Henry S. Grasshorn Gebhardt , Olivier Doré

We present fixed domain asymptotic results that establish consistent estimates of the variance and scale parameters for a Gaussian random field with a geometric anisotropic Mat\'ern autocovariance in dimension $d>4$. When $d<4$ this is…

Statistics Theory · Mathematics 2009-06-23 Ethan Anderes

In the present survey we present some of the recent results concerning the geometry of nodal lines of random Gaussian eigenfunctions (in case of spectral degeneracies) or wavepackets and related issues. The most fundamental example, where…

Mathematical Physics · Physics 2011-03-02 Igor Wigman

In this article, we consider elliptic diffusion problems with an anisotropic random diffusion coefficient. We model the notable direction in terms of a random vector field and derive regularity results for the solution's dependence on the…

Numerical Analysis · Mathematics 2016-07-20 Helmut Harbrecht , Michael Peters , Marc Schmidlin

Gaussian Markov random fields (GMRFs) are frequently used as computationally efficient models in spatial statistics. Unfortunately, it has traditionally been difficult to link GMRFs with the more traditional Gaussian random field models as…

Statistics Theory · Mathematics 2011-11-01 Daniel Simpson , Finn Lindgren , Håvard Rue
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