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We consider a simple initial-boundary-value problem for the shallow water equations in one space dimension, and also the analogous problem for a symmetric variant of the system. Assuming smoothness of solutions, we discretize these problems…

Numerical Analysis · Mathematics 2014-11-26 D. C. Antonopoulos , V. A. Dougalis

In this paper we propose a pressure robust staggered discontinuous Galerkin method for the Stokes equations on general polygonal meshes by using piecewise constant approximations. We modify the right hand side of the body force in the…

Numerical Analysis · Mathematics 2020-07-02 Lina Zhao , Eun-Jae Park , Eric Chung

We study the time-dependent Navier-Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion, and…

Numerical Analysis · Mathematics 2026-01-14 Bedřich Sousedík , Randy Price

A superconvergence error estimate for the gradient approximation of the second order elliptic problem in three dimensions is analyzed by using weak Galerkin finite element scheme on the uniform and non-uniform cubic partitions. Due to the…

Numerical Analysis · Mathematics 2018-10-19 Dan Li , Yufeng Nie , Chunmei Wang

The law of the iterated logarithm (LIL) for the time-homogeneous Markov process with a unique invariant measure characterizes the almost sure maximum possible fluctuation of time averages around the ergodic limit. Whether a numerical…

Numerical Analysis · Mathematics 2025-11-10 Chuchu Chen , Xinyu Chen , Jialin Hong

Over the last few years there have been dramatic advances in our understanding of mathematical and computational models of complex systems in the presence of uncertainty. This has led to a growth in the area of uncertainty quantification as…

Numerical Analysis · Mathematics 2013-06-05 Maziar Raissi , Padmanabhan Seshaiyer

This paper, as the sequel to previous work, develops numerical schemes for fractional diffusion equations on a two-dimensional finite domain with triangular meshes. We adopt the nodal discontinuous Galerkin methods for the full spatial…

Numerical Analysis · Mathematics 2015-07-14 Liangliang Qiu , Weihua Deng , Jan Hesthaven

In this paper we construct space-time full discretizations of stochastic Allen-Cahn equations driven by space-time white noise on 2D torus. The approximations are implemented by tamed exponential Euler discretization in time and spectral…

Probability · Mathematics 2024-06-07 Ting Ma , Lifei Wang , Huanyu Yang

Maxwell's equations are considered with transparent boundary conditions, for initial conditions and inhomogeneity having support in a bounded, not necessarily convex three-dimensional domain or in a collection of such domains. The numerical…

Numerical Analysis · Mathematics 2020-10-21 Balázs Kovács , Christian Lubich

A numerical method based on the hybridizable discontinuous Galerkin method in space and backward Euler in time is formulated and analyzed for solving the miscible displacement problem. Under low regularity assumptions, convergence is…

Numerical Analysis · Mathematics 2025-05-19 Keegan L. A. Kirk , Beatrice Riviere

This paper introduces new discretization schemes for time-harmonic Maxwell equations in a connected domain by using the weak Galerkin (WG) finite element method. The corresponding WG algorithms are analyzed for their stability and…

Numerical Analysis · Mathematics 2016-10-17 Chunmei Wang

We consider a simple initial-boundary-value problem for the shallow water equations in one space dimension. We discretize the problem in space by the standard Galerkin finite element method on a quasiuniform mesh and in time by the…

Numerical Analysis · Mathematics 2018-10-26 D. c. Antonopoulos , V. a. Dougalis , G. Kounadis

We introduce an ergodic approach to the study of {\em joint normality} of representations of numbers. For example, we show that for any integer $b \geq 2$ almost every number $x \in [0,1)$ is jointly normal with respect to the $b$-expansion…

Dynamical Systems · Mathematics 2023-11-09 Vitaly Bergelson , Younghwan Son

Inspired by the stochastic particle method, this paper establishes an easily implementable explicit numerical method for McKean-Vlasov stochastic differential equations (MV-SDEs) with superlinear growth coefficients. The paper establishes…

Probability · Mathematics 2025-12-25 Yuanping Cui , Xiaoyue Li , Yi Liu , Fengyu Wang

In the present work, strong approximation errors are analyzed for both the spatial semi-discretization and the spatio-temporal fully discretization of stochastic wave equations (SWEs) with cubic polynomial nonlinearities and additive…

Numerical Analysis · Mathematics 2024-11-08 Ruisheng Qi , Xiaojie Wang

We design a fully implementable scheme to compute the invariant distribution of ergodic McKean-Vlasov SDE satisfying a uniform confluence property. Under natural conditions, we prove various convergence results notably we obtain rates for…

Probability · Mathematics 2025-02-13 Jean-François Chassagneux , Gilles Pagès

This paper presents a new numerical method for the compressible Navier-Stokes equations governing the flow of an ideal isentropic gas. To approximate the continuity equation, the method utilizes a discontinuous Galerkin discretization on…

Numerical Analysis · Mathematics 2012-06-21 Trygve K. Karper

We consider time-harmonic Maxwell's equations set in an heterogeneous medium with perfectly conducting boundary conditions. Given a divergence-free right-hand side lying in $L^2$, we provide a frequency-explicit approximability estimate…

Numerical Analysis · Mathematics 2022-08-03 T. Chaumont-Frelet , P. Vega

This paper is concerned with developing accurate and efficient numerical methods for fully nonlinear second order elliptic and parabolic partial differential equations (PDEs) in multiple spatial dimensions. It presents a general framework…

Numerical Analysis · Mathematics 2018-01-19 Xiaobing Feng , Thomas Lewis

We analyze the behavior of stochastic approximation algorithms where iterates, in expectation, progress towards an objective at each step. When progress is proportional to the step size of the algorithm, we prove exponential concentration…

Machine Learning · Statistics 2024-03-26 Kody Law , Neil Walton , Shangda Yang