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We analyze a discretization method for solving nonlinear integral equations that contain multiple integrals. These equations include integral equations with a Volterra series, instead of a single integral term, on one side of the equation.…

Numerical Analysis · Mathematics 2010-02-04 S. A. Belbas , Yuriy Bulka

We apply second order finite difference to calculate the lowest eigenvalues of the Helmholtz equation, for complicated non-tensor domains in the plane, using different grids which sample exactly the border of the domain. We show that the…

Computational Physics · Physics 2016-03-23 Paolo Amore , John P. Boyd , Francisco M. Fernandez , Boris Rösler

Fourth-order differential equations play an important role in many applications in science and engineering. In this paper, we present a three-field mixed finite-element formulation for fourth-order problems, with a focus on the effective…

Numerical Analysis · Mathematics 2022-10-13 Patrick E. Farrell , Abdalaziz Hamdan , Scott P. MacLachlan

This paper presents a universal numerical scheme tailored for tackling linear integral, integro-differential, and both initial and boundary value problems of ordinary differential equations. The numerical scheme is readily adapted for…

General Mathematics · Mathematics 2026-01-23 Vladimir Kryzhniy

The main subject of this paper is the study of analytic second order linear partial differential equations. We aim to solve the classical equations and some more, in the real or complex analytical case. This is done by introducing methods…

Dynamical Systems · Mathematics 2019-07-08 Victor León , Bruno Scárdua

Fractal Interpolation has been proposed in the literature as an efficient way to construct closure models for the numerical solution of coarse-grained Navier-Stokes equations. It is based on synthetically generating a scale-invariant…

Fluid Dynamics · Physics 2016-08-16 Sukanta Basu , Efi Foufoula-Georgiou , Fernando Porté-Agel

We propose a new unstructured numerical subgrid method for solving the shallow water equations using a finite volume method with enhanced bathymetry resolution. The method employs an unstructured triangular mesh with support for…

We obtain an explicit error expansion for the solution of Backward Stochastic Differential Equations (BSDEs) using the cubature on Wiener spaces method. The result is proved under a mild strengthening of the assumptions needed for the…

Probability · Mathematics 2019-02-22 Jean-François Chassagneux , Camilo A. Garcia Trillos

Inverse problem or parameter estimation of ordinary differential equations (ODEs), the iterative process of minimizing the mismatch between model-predicted and experimental states by tuning the parameter values within an optimization…

Systems and Control · Electrical Eng. & Systems 2026-04-21 Siddharth Prabhu , Srinivas Rangarajan , Mayuresh Kothare

We present an efficient second-order finite difference scheme for solving the 2D sine-Gordon equation, which can inherit the discrete energy conservation for the undamped model theoretically. Due to the semi-implicit treatment for the…

Numerical Analysis · Mathematics 2017-06-28 Xiaorong Kang , Wenqiang Feng , Kelong Cheng , Chunxiang Guo

In this paper, hybrid and block-pulse functions are used to approximate the solution of a class of Fredholm integro-differential equations that was first studied by Hemeda. By employing suitable approximations, the equation has been…

Functional Analysis · Mathematics 2025-08-27 Aline Hosry , Roger Nakad , Sachin Bhalekar

In this article, we propose a two-grid based adaptive proper orthogonal decomposition (POD) method to solve the time dependent partial differential equations. Based on the error obtained in the coarse grid, we propose an error indicator for…

Numerical Analysis · Mathematics 2020-07-24 Xiaoying Dai , Xiong Kuang , Jack Xin , Aihui Zhou

We present a simple and effective multigrid-based Poisson solver of second-order accuracy in both gravitational potential and forces in terms of the one, two and infinity norms. The method is especially suitable for numerical simulations…

Computational Physics · Physics 2020-03-04 Hsiang-Hsu Wang , Chien-Chang Yen

In this paper we show how to derive regularity for the solution of Kolmogorov PIDEs driven by a vector field which is a second order integro differential operator of affine type. These results are valuable in applications, in particular for…

Probability · Mathematics 2014-06-13 Nicoletta Gabrielli

The development of data-driven approaches for solving differential equations has been followed by a plethora of applications in science and engineering across a multitude of disciplines and remains a central focus of active scientific…

Machine Learning · Computer Science 2024-07-09 Milad Saadat , Deepak Mangal , Safa Jamali

We introduce a numerical method for the solution of the time-dependent Schrodinger equation with a smooth potential, based on its reformulation as a Volterra integral equation. We present versions of the method both for periodic boundary…

Numerical Analysis · Mathematics 2021-08-03 Jason Kaye , Alex Barnett , Leslie Greengard

In this article, a nonlinear fractional Cable equation is solved by a two-grid algorithm combined with finite element (FE) method. A temporal second-order fully discrete two-grid FE scheme, in which the spatial direction is approximated by…

Numerical Analysis · Mathematics 2016-06-14 Yang Liu , Yanwei Du , Hong Li , Jinfeng Wang

We present a novel approach for solving the time-dependent Schr\"{o}dinger equation (TDSE). The method we propose converts the TDSE to an equivalent Volterra integral equation; introducing a global Lagrange interpolation of the integrand…

Numerical Analysis · Mathematics 2023-06-07 Ryan Schneider , Heman Gharibnejad , Barry I. Schneider

In this paper, a reduced-order model (ROM) based on the proper orthogonal decomposition and the discrete empirical interpolation method is proposed for efficiently simulating time-fractional partial differential equations (TFPDEs). Both…

Numerical Analysis · Mathematics 2024-02-07 Hongfei Fu , Hong Wang , Zhu Wang

We generalize the framework of Fredholm Neural Networks, to learn non-expansive integral operators arising in Fredholm Integral Equations (FIEs) of the second kind in arbitrary dimensions. We first present the proposed Fredholm Integral…

Numerical Analysis · Mathematics 2026-04-06 Kyriakos C. Georgiou , Constantinos Siettos , Athanasios N. Yannacopoulos
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