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We introduce generalised finite difference methods for solving fully nonlinear elliptic partial differential equations. Methods are based on piecewise Cartesian meshes augmented by additional points along the boundary. This allows for…

Numerical Analysis · Mathematics 2017-06-26 Brittany D. Froese , Tiago Salvador

A numerical method for solving elliptic PDEs with variable coefficients on two-dimensional domains is presented. The method is based on high-order composite spectral approximations and is designed for problems with smooth solutions. The…

Numerical Analysis · Mathematics 2013-07-11 A. Gillman , P. G. Martinsson

We propose machine learning methods for solving fully nonlinear partial differential equations (PDEs) with convex Hamiltonian. Our algorithms are conducted in two steps. First the PDE is rewritten in its dual stochastic control…

Computational Finance · Quantitative Finance 2022-05-23 William Lefebvre , Grégoire Loeper , Huyên Pham

We present a new method based on functional tensor decomposition and dynamic tensor approximation to compute the solution of a high-dimensional time-dependent nonlinear partial differential equation (PDE). The idea of dynamic approximation…

Numerical Analysis · Mathematics 2021-04-14 Alec Dektor , Daniele Venturi

We obtain new quantitative estimates of the vanishing viscosity approximation for time-dependent, degenerate, Hamilton-Jacobi equations that are neither concave nor convex in the gradient and Hessian entries of the form $\partial_t…

Analysis of PDEs · Mathematics 2025-09-16 Alekos Cecchin , Alessandro Goffi

We propose a collocation method based on multivariate polynomial splines over triangulation or tetrahedralization for the numerical solution of partial differential equations. We start with a detailed explanation of the method for the…

Numerical Analysis · Mathematics 2023-04-18 Ming-Jun Lai , Jinsil Lee

This paper proposes two efficient approximation methods to solve high-dimensional fully nonlinear partial differential equations (NPDEs) and second-order backward stochastic differential equations (2BSDEs), where such high-dimensional fully…

Numerical Analysis · Mathematics 2023-01-18 Xu Xiao , Wenlin Qiu , Omid Nikan

We introduce a method-of-lines formulation of the closest point method, a numerical technique for solving partial differential equations (PDEs) defined on surfaces. This is an embedding method, which uses an implicit representation of the…

Numerical Analysis · Mathematics 2013-07-23 Ingrid von Glehn , Thomas März , Colin B. Macdonald

In the theory and practice of inverse problems for partial differential equations (PDEs) much attention is paid to the problem of the identification of coefficients from some additional information. This work deals with the problem of…

Numerical Analysis · Computer Science 2013-04-23 P. N. Vabishchevich , V. I. Vasil'ev

We introduce a notion of approximate viscosity solution for a class of nonlinear path-dependent PDEs (PPDEs), including the Hamilton-Jacobi-Bellman type equations. Existence, comparaison and stability results are established under fairly…

Analysis of PDEs · Mathematics 2021-09-09 Bruno Bouchard , Grégoire Loeper , Xiaolu Tan

In this study, we concern the multidimensional viscosity solutions theory of a kind of semi-linear partial differential equations (PDEs). A new definition of viscosity solution for this multidimensional semi-linear PDEs which is related to…

Dynamical Systems · Mathematics 2016-08-09 Shuzhen Yang

A bivariate spline method is developed to numerically solve second order elliptic partial differential equations (PDE) in non-divergence form. The existence, uniqueness, stability as well as approximation properties of the discretized…

Numerical Analysis · Mathematics 2017-01-05 Ming-Jun Lai , Chunmei Wang

We study the existence and uniqueness of the stochastic viscosity solutions of fully nonlinear, possibly degenerate, second order stochastic pde with quadratic Hamiltonians associated to a Riemannian geometry. The results are new and extend…

Probability · Mathematics 2016-02-16 Peter K. Friz , Paul Gassiat , Pierre-Louis Lions , Panagiotis E. Souganidis

Randomness is ubiquitous in modern engineering. The uncertainty is often modeled as random coefficients in the differential equations that describe the underlying physics. In this work, we describe a two-step framework for numerically…

Numerical Analysis · Mathematics 2021-02-03 Ting Wang , Jaroslaw Knap

We prove optimal convergence rates for the discretization of a general second-order linear elliptic PDE with an adaptive vertex-centered finite volume scheme. While our prior work Erath and Praetorius [SIAM J. Numer. Anal., 54 (2016), pp.…

Numerical Analysis · Mathematics 2019-07-17 Christoph Erath , Dirk Praetorius

We consider a class of nonlinear elliptic problems associated with models in biophysics, which are described by the Poisson-Boltzmann equation (PBE). We prove mathematical correctness of the problem, study a suitable class of…

Numerical Analysis · Mathematics 2020-12-15 Johannes Kraus , Svetoslav Nakov , Sergey Repin

The curvature estimates of quotient curvature equation do not always exist even for convex setting \cite{GRW}. Thus it is natural question to find other type of elliptic equations possessing curvature estimates. In this paper, we discuss…

Analysis of PDEs · Mathematics 2017-05-30 Chunhe Li , Changyu Ren , Zhizhang Wang

Nonlinear systems of partial differential equations (PDEs) may permit several distinct solutions. The typical current approach to finding distinct solutions is to start Newton's method with many different initial guesses, hoping to find…

Numerical Analysis · Mathematics 2015-07-03 Patrick E. Farrell , Ásgeir Birkisson , Simon W. Funke

This article investigates the numerical approximation of shape optimization problems with PDE constraint on classes of convex domains. The convexity constraint provides a compactness property which implies well posedness of the problem.…

Optimization and Control · Mathematics 2018-10-26 Sören Bartels , Gerd Wachsmuth

In this note we shall introduce a simple, effective numerical method for solving partial differential equations for scalar and vector-valued data defined on surfaces. Even though we shall follow the traditional way to approximate the…

Computational Geometry · Computer Science 2009-07-13 Sheng-Gwo Chen , Mei-Hsiu Chi , Jyh-Yang Wu