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We prove maximum and comparison principles for fractional discrete derivatives in the integers. Regularity results when the space is a mesh of length $h$, and approximation theorems to the continuous fractional derivatives are shown. When…

Analysis of PDEs · Mathematics 2016-05-24 Luciano Abadías , Marta de León-Contreras , José L. Torrea

How many canonical degrees of freedom does a quantum field theory actually use during its Hamiltonian evolution? For a UV/IR-regularised classical scalar field, we address this question directly at the level of phase-space dynamics by…

High Energy Physics - Theory · Physics 2026-04-10 Oliver Friedrich , Kristina Giesel , Varun Kushwaha

In the homogenization of divergence-form equations with random coefficients, a central role is played by the corrector. We focus on a discrete space setting and on dimension 3 and more. Completing the argument started in previous work, we…

Analysis of PDEs · Mathematics 2015-02-27 Jean-Christophe Mourrat , James Nolen

We study real left-invariant spin Gaussian fields on $SO(3)$, a special class of non-isotropic random fields used to model the polarization of the Cosmic Microwave Background. Leveraging recent results from "New chaos decomposition of…

Probability · Mathematics 2025-07-14 Francesca Pistolato , Michele Stecconi

The subject of this work is a new stochastic Galerkin method for second-order elliptic partial differential equations with random diffusion coefficients. It combines operator compression in the stochastic variables with tree-based spline…

Numerical Analysis · Mathematics 2022-06-02 Markus Bachmayr , Igor Voulis

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

We show that if an interlacing particle system in a two-dimensional lattice is a determinantal point process, and the correlation kernel can be expressed as a double integral with certain technical assumptions, then the moments of the…

Mathematical Physics · Physics 2014-08-26 Jeffrey Kuan

We consider the spectral definition of the fractional Laplace operator and study a basic linear problem involving this operator and singular forcing. In two dimensions, we introduce an appropriate weak formulation in fractional Sobolev…

Numerical Analysis · Mathematics 2026-02-13 Enrique Otarola , Abner J. Salgado

In this paper, we develop a sliding method for the fractional Laplacian. We first obtain the key ingredients needed in the sliding method either in a bounded domain or in the whole space, such as narrow region principles and maximum…

Analysis of PDEs · Mathematics 2019-12-03 Leyun Wu , Wenxiong Chen

Gaussian random fields are popular models for spatially varying uncertainties, arising for instance in geotechnical engineering, hydrology or image processing. A Gaussian random field is fully characterised by its mean function and…

Numerical Analysis · Mathematics 2019-02-19 Jonas Latz , Marvin Eisenberger , Elisabeth Ullmann

The Discrete Gaussian model is the lattice Gaussian free field conditioned to be integer-valued. In two dimensions, at sufficiently high temperature, we show that the scaling limit of the infinite-volume gradient Gibbs state with zero mean…

Probability · Mathematics 2024-07-11 Roland Bauerschmidt , Jiwoon Park , Pierre-François Rodriguez

A variational method is discussed, extending the Gaussian effective potential to higher orders. The single variational parameter is replaced by trial unknown two-point functions, with infinite variational parameters to be optimized by the…

High Energy Physics - Phenomenology · Physics 2013-09-30 Fabio Siringo

This paper considers a multivariate spatial random field, with each component having univariate marginal distributions of the skew-Gaussian type. We assume that the field is defined spatially on the unit sphere embedded in $\mathbb{R}^3$,…

Statistics Theory · Mathematics 2017-10-05 Alfredo Alegría , Sandra Caro , Moreno Bevilacqua , Emilio Porcu , Jorge Clarke

In a recent work Levine et al. (2015) prove that the odometer function of a divisible sandpile model on a finite graph can be expressed as a shifted discrete bilaplacian Gaussian field. For the discrete torus, they suggest the possibility…

Probability · Mathematics 2017-11-29 Alessandra Cipriani , Rajat Subhra Hazra , Wioletta M. Ruszel

In this paper we develop a new renormalization group method, which is based on conditional expectations and harmonic extensions, to study functional integrals related with small perturbations of Gaussian fields. In this new method one…

Mathematical Physics · Physics 2014-12-16 Hao Shen

We advance scale-invariance arguments for systems that are governed (or approximated) by a $q-$Gaussian distribution, i.e., a power law distribution with exponent $Q=1/(1-q); q \in \mathbb{R}$. The ensuing line of reasoning is then compared…

Statistical Mechanics · Physics 2009-11-11 C. Vignat , A. Plastino

We prove that the distribution density of any non-constant polynomial $f(\xi_1,\xi_2,\ldots)$ of degree $d$ in independent standard Gaussian random variables $\xi$ (possibly, in infinitely many variables) always belongs to the…

Probability · Mathematics 2016-05-03 Vladimir I. Bogachev , Egor D. Kosov , Georgii I. Zelenov

We collect some peculiarities of higher-order fractional Laplacians $(-\Delta)^s$, $s>1$, with special attention to the range $s\in(1,2)$, which show their oscillatory nature. These include the failure of the polarization and…

Analysis of PDEs · Mathematics 2022-05-26 Nicola Abatangelo , Sven Jarohs

We consider gradient models on the lattice $Z^d$. These models serve as effective models for interfaces and are also known as continuous Ising models. The height of the interface is modelled by a random field with an energy which is a…

Mathematical Physics · Physics 2020-07-22 Susanne Hilger

We consider the problem of learning a Gaussian variational approximation to the posterior distribution for a high-dimensional parameter, where we impose sparsity in the precision matrix to reflect appropriate conditional independence…

Computation · Statistics 2019-04-23 Linda S. L. Tan , David J. Nott