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This paper studies a family of convolution quadratures, a numerical technique for efficient evaluation of convolution integrals. We employ the block generalized Adams method to discretize the underlying initial value problem, departing from…

Numerical Analysis · Mathematics 2024-07-11 Ling Liu , Junjie Ma

We study the application of the generalized convolution quadrature (gCQ) based on Runge--Kutta methods to approximate the solution of an important class of sectorial problems. The gCQ generalizes Lubich's original convolution quadrature…

Numerical Analysis · Mathematics 2025-06-27 Jing Guo , Maria Lopez-Fernandez

We consider the application of the generalized Convolution Quadrature (gCQ) to approximate the solution of an important class of sectorial problems. The gCQ is a generalization of Lubich's Convolution Quadrature (CQ) that allows for…

Numerical Analysis · Mathematics 2024-12-05 Jing Guo , Maria Lopez-Fernandez

The exponential trapezoidal rule is proposed and analyzed for the numerical integration of semilinear integro-differential equations. Although the method is implicit, the numerical solution is easily obtained by standard fixed-point…

Numerical Analysis · Mathematics 2024-03-12 Alexander Ostermann , Nasrin Vaisi

This article is concerned with a new method for the approximate evaluation of Fourier sine and cosine transforms. We develop and analyse a new quadrature rule for Fourier sine and cosine transforms involving transforming the integral to one…

Numerical Analysis · Mathematics 2007-05-23 Patrick McLean

A randomised trapezoidal quadrature rule is proposed for continuous functions which enjoys less regularity than commonly required. Indeed, we consider functions in some fractional Sobolev space. Various error bounds for this randomised rule…

Numerical Analysis · Mathematics 2020-12-03 Yue Wu

In this article we analyze a generalized trapezoidal rule for initial value problems with piecewise smooth right hand side \(F:\R^n\to\R^n\). When applied to such a problem the classical trapezoidal rule suffers from a loss of accuracy if…

Numerical Analysis · Mathematics 2017-01-04 Andreas Griewank , Richard Hasenfelder , Manuel Radons , Tom Streubel

Rough paths techniques give the ability to define solutions of stochastic differential equations driven by signals $X$ which are not semimartingales and whose $p$-variation is finite only for large values of $p$. In this context, rough…

Probability · Mathematics 2020-05-15 Yanghui Liu , Zachary Selk , Samy Tindel

In this paper a novel contour integral method is proposed for linear convection-diffusion equations. The method is based on the inversion of the Laplace transform and makes use of a contour given by an elliptic arc joined symmetrically to…

Numerical Analysis · Mathematics 2019-07-29 Nicola Guglielmi , Maria López-Fernández , Giancarlo Nino

We present convergence theory for corrected quadrature rules on uniform Cartesian grids for functions with a point singularity. We begin by deriving an error estimate for the punctured trapezoidal rule, and then derive error expansions. We…

Numerical Analysis · Mathematics 2022-08-30 Federico Izzo , Olof Runborg , Richard Tsai

The quadrature error associated with a regular quadrature rule for evaluation of a layer potential increases rapidly when the evaluation point approaches the surface and the integral becomes nearly singular. Error estimates are needed to…

Numerical Analysis · Mathematics 2022-01-20 Ludvig af Klinteberg , Chiara Sorgentone , Anna-Karin Tornberg

In this article, we develop a new method to approximate numerically the fractional Laplacian of functions defined on $\mathbb R$, as well as some more general singular integrals. After mapping $\mathbb R$ into a finite interval, we…

Numerical Analysis · Mathematics 2022-12-13 Jorge Cayama , Carlota M. Cuesta , Francisco de la Hoz , Carlos J. Garcia-Cervera

A class of numerical quadrature rules is derived, with equally-spaced nodes, and unit weights except at a few points at each end of the series, for which "corrections" (not using any further information about the integrand) are added to the…

History and Overview · Mathematics 2025-12-19 Gavin R. Putland

We consider a novel way of discretizing wave scattering problems using the general formalism of convolution quadrature, but instead of reducing the timestep size ($h$-method), we achieve accuracy by increasing the order of the method…

Numerical Analysis · Mathematics 2024-10-25 Alexander Rieder

This document is made up of two different units. One of them is a regular terse research article, whereas the other one is the detailed and independently written explanations for the paper, so that readers of the short paper do not need to…

Numerical Analysis · Mathematics 2019-03-22 Hasan Eruslu , Francisco-Javier Sayas

We present new higher-order quadratures for a family of boundary integral operators re-derived using the approach introduced in [Kublik, Tanushev, and Tsai - J. Comp. Phys. 247: 279-311, 2013]. In this formulation, a boundary integral over…

Numerical Analysis · Mathematics 2022-04-04 Federico Izzo , Olof Runborg , Richard Tsai

Gauss-Legendre quadrature and the trapezoidal rule are powerful tools for numerical integration of analytic functions. For nearly singular problems, however, these standard methods become unacceptably slow. We discuss and generalize some…

Numerical Analysis · Mathematics 2022-10-19 William Mitchell , Abbie Natkin , Paige Robertson , Marika Sullivan , Xuechen Yu , Chenxin Zhu

In this work, we extend the fractional linear multistep methods in [C. Lubich, SIAM J. Math. Anal., 17 (1986), pp.704--719] to the tempered fractional integral and derivative operators in the sense that the tempered fractional derivative…

Numerical Analysis · Mathematics 2018-12-11 Ling Guo , Fanhai Zeng , Ian Turner , Kevin Burrage , George Em Karniadakis

We study the systematic numerical approximation of Maxwell's equations in dispersive media. Two discretization strategies are considered, one based on a traditional leapfrog time integration method and the other based on convolution…

Numerical Analysis · Mathematics 2020-04-02 Jürgen Dölz , Herbert Egger , Vsevolod Shashkov

Multivariate generalized Gamma convolutions are distributions defined by a convolutional semi-parametric structure. Their flexible dependence structures, the marginal possibilities and their useful convolutional expression make them…

Statistics Theory · Mathematics 2022-03-28 Oskar Laverny
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