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We construct classes of homogeneous random fields on a three-dimensional Euclidean space that take values in linear spaces of tensors of a fixed rank and are isotropic with respect to a fixed orthogonal representation of the group of…

Probability · Mathematics 2018-05-04 Nikolai Leonenko , Anatoliy Malyarenko

We are concerned with the homogenization of second-order linear elliptic equations with random coefficient fields. For symmetric coefficient fields with only short-range correlations, quantified through a logarithmic Sobolev inequality for…

Analysis of PDEs · Mathematics 2016-11-08 Peter Bella , Benjamin Fehrman , Julian Fischer , Felix Otto

We prove estimates for the variation of the eigenvalues of uniformly elliptic operators with homogeneous Dirichlet or Neumann boundary conditions upon variation of the open set on which an operator is defined. We consider operators of…

Spectral Theory · Mathematics 2012-04-16 Victor I. Burenkov , Pier Domenico Lamberti

We introduce a stochastic analysis of Grassmann random variables suitable for the stochastic quantization of Euclidean fermionic quantum field theories. Analysis on Grassmann algebras is developed here from the point of view of quantum…

Probability · Mathematics 2022-02-02 Sergio Albeverio , Luigi Borasi , Francesco C. De Vecchi , Massimiliano Gubinelli

We use the stochastic quantization method to study systems with complex valued path integral weights. We assume a Langevin equation with a memory kernel and Einstein's relations with colored noise. The equilibrium solution of this…

High Energy Physics - Theory · Physics 2008-11-26 G. Menezes , N. F. Svaiter

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

Random fields in nature often have, to a good approximation, Gaussian characteristics. We present the mathematical framework for a new and simple method for investigating the non-Gaussian contributions, based on counting the maxima and…

Statistical Mechanics · Physics 2012-10-26 T. H. Beuman , A. M. Turner , V. Vitelli

The purpose of this paper is to establish the theory of stochastic pseudo-differential operators and give its applications in stochastic partial differential equations. First, we introduce some concepts on stochastic pseudo-differential…

Analysis of PDEs · Mathematics 2011-03-02 Xu Liu , Xu Zhang

This work is concerned with existence of weak solutions to discon- tinuous stochastic differential equations driven by multiplicative Gaus- sian noise and sliding mode control dynamics generated by stochastic differential equations with…

Optimization and Control · Mathematics 2015-04-27 Viorel Barbu , Stefano Bonaccorsi , Luciano Tubaro

This work addresses the finite-horizon robust covariance control problem for discrete-time, partially observable, linear system affected by random zero mean noise and deterministic but unknown disturbances restricted to lie in what is…

Optimization and Control · Mathematics 2020-07-02 Georgios Kotsalis , Guanghui Lan , Arkadi Nemirovski

Motivated by many applications in complex domains with boundaries exposed to large topological changes or deformations, fictitious domain methods regard the actual domain of interest as being embedded in a fixed Cartesian background. This…

Numerical Analysis · Mathematics 2020-03-17 Georgios Katsouleas , Efthymios N. Karatzas , Fotios Travlopanos

In this paper we discuss the existence and regularity of solutions of strongly indefinite systems involving fractional elliptic operators on a smooth bounded domain $\Omega$ in $\R^n$.

Analysis of PDEs · Mathematics 2017-06-06 Edir Leite

We examine the question of whether the formal expressions of equilibrium statistical mechanics can be applied to time independent non-dissipative systems that are not in true thermodynamic equilibrium and are nonergodic. By assuming the…

Statistical Mechanics · Physics 2007-11-09 Stephen R. Williams , Denis J. Evans

We derive optimal estimates in stochastic homogenization of linear elliptic equations in divergence form in dimensions $d\ge 2$. In previous works we studied the model problem of a discrete elliptic equation on $\mathbb{Z}^d$. Under the…

Analysis of PDEs · Mathematics 2014-09-03 Antoine Gloria , Felix Otto

We establish optimal L^p bounds for the nontangential maximal function of the gradient of the solution to a second order elliptic operator in divergence form, possibly non-symmetric, with bounded measurable coefficients independent of the…

Analysis of PDEs · Mathematics 2007-05-23 Carlos E. Kenig , David J. Rule

Stochastic Einstein equations are considered when 3D space metric $\gamma_{ij}$ are stochastic functions. The probability density for the stochastic quantities is connected with the Perelman's entropy functional. As an example, the Friedman…

General Relativity and Quantum Cosmology · Physics 2015-05-19 Vladimir Dzhunushaliev

In this paper, we propose the uncertain volatility models with stochastic bounds. Like the regular uncertain volatility models, we know only that the true model lies in a family of progressively measurable and bounded processes, but instead…

Mathematical Finance · Quantitative Finance 2017-02-17 Jean-Pierre Fouque , Ning Ning

This paper focuses on the uniform boundary estimates in homogenization of a family of higher order elliptic operators $\mathcal{L}_\epsilon$, with rapidly oscillating periodic coefficients. We derive uniform boundary $C^{m-1,\lambda}…

Analysis of PDEs · Mathematics 2017-09-14 Weisheng Niu , Yao Xu

We investigate the realization of a myriad of general local and nonlocal inhomogeneous elliptic and parabolic boundary value problems over classes of irregular regions. We present a unified approach in which either local or nonlocal…

Analysis of PDEs · Mathematics 2026-02-10 Maria R. Lancia , Alejandro Vélez-Santiago

We introduce computational methods that allow for effective estimation of a flexible, parametric non-stationary spatial model when the field size is too large to compute the multivariate normal likelihood directly. In this method, the field…

Computation · Statistics 2018-09-20 Amanda Muyskens , Joseph Guinness , Montserrat Fuentes