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We propose a stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs. Our approach is based on a bi-objective viewpoint of chance-constrained programs that seeks solutions on the…

Optimization and Control · Mathematics 2020-05-29 Rohit Kannan , James Luedtke

The macroscopic behavior of dissipative stochastic partial differential equations usually can be described by a finite dimensional system. This article proves that a macroscopic reduced model may be constructed for stochastic…

Mathematical Physics · Physics 2008-12-11 Wei Wang , A. J. Roberts

We consider an initial-boundary value problem for $\partial_tu-\partial_t^{-\alpha}\nabla^2u=f(t)$, that is, for a fractional diffusion ($-1<\alpha<0$) or wave ($0<\alpha<1$) equation. A numerical solution is found by applying a…

Numerical Analysis · Mathematics 2016-02-02 Kassem Mustapha , William McLean

We introduce forward-backward stochastic differential equations, highlighting the connection between solutions of these and solutions of partial differential equations, related by the Feynman-Kac theorem. We review the technique of…

Numerical Analysis · Mathematics 2025-02-18 Oliver Sheridan-Methven

Stochastic Galerkin methods can quantify uncertainty at a fraction of the computational expense of conventional Monte Carlo techniques, but such methods have rarely been studied for modelling shallow water flows. Existing stochastic shallow…

Numerical Analysis · Mathematics 2019-07-16 James Shaw , Georges Kesserwani

This paper deals with the weak error estimates of the exponential Euler method for semi-linear stochastic partial differential equations (SPDEs). A weak error representation formula is first derived for the exponential integrator scheme in…

Numerical Analysis · Mathematics 2015-06-23 Xiaojie Wang

We consider a linear elliptic partial differential equation (PDE) with a generic uniformly bounded parametric coefficient. The solution to this PDE problem is approximated in the framework of stochastic Galerkin finite element methods. We…

Numerical Analysis · Mathematics 2020-06-05 Alex Bespalov , Feng Xu

Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. In case of repeated observations of time series for several experimental units, it is often the case that some of the…

Methodology · Statistics 2024-09-06 Fernando Baltazar-Larios , Mogens Bladt , Michael Sørensen

We establish a quantitfied overdamped limit for kinetic Vlasov-Fokker-Planck equations with nonlocal interaction forces. We provide explicit bounds on the error between solutions of that kinetic equation and the limiting equation, which is…

Analysis of PDEs · Mathematics 2021-06-01 Young-Pil Choi , Oliver Tse

The generalized polynomial chaos method is applied to the Buckley-Leverett equation. We consider a spatially homogeneous domain modeled as a random field. The problem is projected onto stochastic basis functions which yields an extended…

Numerical Analysis · Mathematics 2016-08-24 Per Pettersson , Hamdi A. Tchelepi

Error bounds for fully discrete schemes for the evolutionary incompressible Navier--Stokes equations are derived in this paper. For the time integration we apply BDF-$q$ methods, $q\le 5$, for which error bounds for $q\ge 3$ cannot be found…

Numerical Analysis · Mathematics 2025-06-23 Bosco García-Archilla , V. John , Julia Novo

In this paper we study a sharp interface limit for a stochastic reaction-diffusion equation. We consider the case that the noise is a space-time white noise multiplied by a small parameter and a smooth function which has a compact support.…

Probability · Mathematics 2016-10-25 Kai Lee

The Nitsche method is a method of "weak imposition" of the inhomogeneous Dirichlet boundary conditions for partial differential equations. This paper explains stability and convergence study of the Nitsche method applied to evolutionary…

Numerical Analysis · Mathematics 2018-03-28 Yuki Ueda , Norikazu Saito

In computational system biology, the mesoscopic model of reaction-diffusion kinetics is described by a continuous time, discrete space Markov process. To simulate diffusion stochastically, the jump coefficients are obtained by a…

Numerical Analysis · Mathematics 2018-02-19 Lina Meinecke , Stefan Engblom , Andreas Hellander , Per Lötstedt

In this paper, we use Fourier analysis to study the superconvergence of the semi-discrete discontinuous Galerkin method for scalar linear advection equations in one spatial dimension. The error bounds and asymptotic errors are derived for…

Numerical Analysis · Mathematics 2021-02-02 Sirvan Rahmati , Tianshi Lu

We consider a special type of fast reaction-diffusion systems in which the coefficients of the reaction terms of the two substances are much larger than those of the diffusion terms while the diffusive motion to the substrate is negligible.…

Numerical Analysis · Mathematics 2024-04-30 Yu Zhao , Zhennan Zhou

We study the numerical approximation of singularly perturbed convection-diffusion problems on one-dimensional pipe networks. In the vanishing diffusion limit, the number and type of boundary conditions and coupling conditions at network…

Numerical Analysis · Mathematics 2022-09-12 Herbert Egger , Nora Philippi

This work considers the Galerkin approximation and analysis for a hyperbolic integrodifferential equation, where the non-positive variable-sign kernel and nonlinear-nonlocal damping with both the weak and viscous damping effects are…

Numerical Analysis · Mathematics 2025-02-21 Wenlin Qiu , Xiangcheng Zheng , Kassem Mustapha

In this study, we examine numerical approximations for 2nd-order linear-nonlinear differential equations with diverse boundary conditions, followed by the residual corrections of the first approximations. We first obtain numerical results…

Numerical Analysis · Mathematics 2023-06-19 Shovan Sourav Datta Pranta , Md. Shafiqul Islam

Prediction via deterministic continuous-time models will always be subject to model error, for example due to unexplainable phenomena, uncertainties in any data driving the model, or discretisation/resolution issues. In this paper, we build…

Dynamical Systems · Mathematics 2025-06-30 Liam Blake , John Maclean , Sanjeeva Balasuriya
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