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We review the stability properties of several discretizations of the Helmholtz equation at large wavenumbers. For a model problem in a polygon, a complete $k$-explicit stability (including $k$-explicit stability of the continuous problem)…

Numerical Analysis · Mathematics 2015-03-31 Sofi Esterhazy , Jens Markus Melenk

The Calder\'on formulas (i.e., the combination of single-layer and hyper-singular boundary integral operators) have been widely utilized in the process of constructing valid boundary integral equation systems which could possess highly…

Analysis of PDEs · Mathematics 2021-08-26 Liwei Xu , Tao Yin

In this paper, a high-order exponential scheme is developed to solve the 1D unsteady convection-diffusion equation with Neumann boundary conditions. The present method applies fourth-order compact exponential difference scheme in spatial…

Fluid Dynamics · Physics 2018-05-16 Yucheng Fu , Zhenfu Tian , Yang Liu

I introduce an innovative methodology for deriving numerical models of systems of partial differential equations which exhibit the evolution of spatial patterns. The new approach directly produces a discretisation for the evolution of the…

Numerical Analysis · Mathematics 2025-10-20 A. J. Roberts

A fast method for solving boundary integral equations with the generalized Neumann kernel and the adjoint generalized Neumann kernel is presented. The method is based on discretizing the integral equations by the Nystr\"om method with the…

Numerical Analysis · Mathematics 2015-04-10 Mohamed M. S. Nasser

We study the approximation of the spectrum of a second-order elliptic differential operator by the Hybrid High-Order (HHO) method. The HHO method is formulated using cell and face unknowns which are polynomials of some degree $k\geq0$. The…

Numerical Analysis · Mathematics 2018-07-23 Victor Calo , Matteo Cicuttin , Quanling Deng , Alexandre Ern

We establish a canonical normal form for the iterates of a curved differential in curved differential algebras (CDA). This operator calculus clarifies the underlying algebraic structure of CDAs and bypasses the need for complex…

Algebraic Topology · Mathematics 2026-04-17 Mauricio Angel

In this paper, optimal control problems governed by diffusion equations with Dirichlet and Neumann boundary conditions are investigated in the framework of the gradient discretisation method. Gradient schemes are defined for the optimality…

Numerical Analysis · Mathematics 2018-10-09 Jerome Droniou , Neela Nataraj , Devika Shylaja

We present an algorithm for constructing numerical solutions to one--dimensional nonlinear, variable coefficient boundary value problems. This scheme is based upon applying the Homotopy Analysis Method (HAM) to decompose a nonlinear…

Numerical Analysis · Mathematics 2019-03-27 Andrew C. Cullen , Simon R. Clarke

Getting standard multigrid to work efficiently for the high-frequency Helmholtz equation has been an open problem in applied mathematics for years. Much effort has been dedicated to finding solution methods which can use multigrid…

Numerical Analysis · Mathematics 2023-08-28 Vandana Dwarka , Cornelis Vuik

This note is about promoting singularity subtraction as a helpful tool in the discretization of singular integral operators on curved surfaces. Singular and nearly singular kernels are expanded in series whose terms are integrated on…

Numerical Analysis · Mathematics 2013-01-31 Johan Helsing

Discrete regularization methods are often applied for obtaining stable approximate solutions for ill-posed operator equations $Tx=y$, where $T: X\to Y$ is a bounded operator between Hilbert spaces with non-closed range $R(T)$ and $y\in…

Functional Analysis · Mathematics 2016-07-01 M Thamban Nair

In the field of Domain Decomposition (DD), Optimized Schwarz Method (OSM) appears to be one of the prominent techniques to solve large scale time-harmonic wave propagation problems. It is based on appropriate transmission conditions using…

Numerical Analysis · Mathematics 2021-08-31 Xavier Claeys , Emile Parolin

In this paper we extend Sylvester's approach via upper triangular compact operators to establish the discreteness of transmission eigenvalues for higher-order main terms and higher-order perturbations. The coefficients of the perturbations…

Spectral Theory · Mathematics 2015-12-18 Andoni García , Esa V. Vesalainen , Miren Zubeldia

In this work, we investigate the discrete Calder\'{o}n problem on grid graphs of dimension three or higher, formed by hypercubic structures. The discrete Calder\'{o}n problem is concerned with determining whether the discrete…

Mathematical Physics · Physics 2026-03-09 Maolin Deng , Bangti Jin

We study Nystr\"om type subsampling approaches to large scale kernel methods, and prove learning bounds in the statistical learning setting, where random sampling and high probability estimates are considered. In particular, we prove that…

Machine Learning · Statistics 2016-03-18 Alessandro Rudi , Raffaello Camoriano , Lorenzo Rosasco

We provide sufficient conditions for vector-valued Fredholm integral operators and their commonly used spatial discretizations to be positive in terms of an order relation induced by a corresponding order cone. It turns out that reasonable…

Dynamical Systems · Mathematics 2022-09-07 Magdalena Nockowska-Rosiak , Christian Pötzsche

In this paper, we consider a new approach for semi-discretization in time and spatial discretization of a class of semi-linear stochastic partial differential equations (SPDEs) with multiplicative noise. The drift term of the SPDEs is only…

Numerical Analysis · Mathematics 2023-07-10 Yukun Li , Liet Vo , Guanqian Wang

Highly accurate simulations of problems including second derivatives on complex geometries are of primary interest in academia and industry. Consider for example the Navier-Stokes equations or wave propagation problems of acoustic or…

Numerical Analysis · Mathematics 2024-04-16 Gustav Eriksson

Neural operators have emerged as a powerful, discretization-invariant framework for solving partial differential equations (PDEs). Although established approaches like the Deep Operator Network (DeepONet) have successfully achieved…

Machine Learning · Computer Science 2026-05-20 Abderrahim Bendahi , Adrien Fradin , Johan Peralez , Julie Digne , Madiha Nadri
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