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The application of the approximation-operational approach to solving linear differential equations of fractional order with variable coefficients is considered. It is shown that the method can also be applied to solving differential…

Dynamical Systems · Mathematics 2020-06-04 Oleksii V. Vasyliev

We introduce and analyze an explicit formulation of fractional powers of the Lam\'e-Navier system of partial differential operators. We show that this fractional Lam\'e-Navier operator is a nonlocal integro-differential operator that…

Analysis of PDEs · Mathematics 2023-01-10 James M. Scott

A development of an inverse first-order divided difference operator for functions of several variables is presented. Two generalized derivative-free algorithms builded up from Ostrowski's method for solving systems of nonlinear equations…

Numerical Analysis · Mathematics 2011-10-12 Miquel Grau-Sánchez , Miquel Noguera , Sergio Amat

We propose a method to reduce the computational effort to solve a partial differential equation on a given domain. The main idea is to split the domain of interest in two subdomains, and to use different approximation methods in each of the…

Classical Physics · Physics 2007-12-06 Marcelo Buffoni , Haysam Telib , Angelo Iollo

We establish sharp upper and lower bounds on the heat kernel of the fractional Laplace operator perturbed by Hardy-type drift by transferring it to appropriate weighted space with singular weight.

Analysis of PDEs · Mathematics 2020-07-03 D. Kinzebulatov , Yu. A. Semenov

We introduce a method that combines neural operators, physics-informed machine learning, and standard numerical methods for solving PDEs. The proposed approach extends each of the aforementioned methods and unifies them within a single…

Computational Engineering, Finance, and Science · Computer Science 2025-12-02 Shahed Rezaei , Reza Najian Asl , Kianoosh Taghikhani , Ahmad Moeineddin , Michael Kaliske , Markus Apel

This work is devoted to the study of the existence of at least one weak solution to nonlocal equations involving a general integro-differential operator of fractional type. As a special case, we derive an existence theorem for the…

Analysis of PDEs · Mathematics 2020-04-22 Giovanni Molica Bisci , Dušan D. Repovš

We consider the fractional elliptic problem with Dirichlet boundary conditions on a bounded and convex domain $D$ of $\mathbb{R}^d$, with $d \geq 2$. In this paper, we perform a stochastic gradient descent algorithm that approximates the…

Analysis of PDEs · Mathematics 2023-09-01 Nicolás Valenzuela

We deal with the higher-order fractional Laplacians by two methods: the integral method and the system method. The former depends on the integral equation equivalent to the differential equation. The latter works directly on the…

Analysis of PDEs · Mathematics 2018-02-07 Ran Zhuo , Yan Li

We propose a fast collocation method based on Krylov subspace iterative solver on general nonuniform grids for the fractional Laplacian problem, in which the fractional operator is presented in a singular integral formulation. The method is…

Numerical Analysis · Mathematics 2025-11-13 Meijie Kong , Hongfei Fu

The stochastic partial differential equation (SPDE) approach is widely used for modeling large spatial datasets. It is based on representing a Gaussian random field $u$ on $\mathbb{R}^d$ as the solution of an elliptic SPDE $L^\beta u =…

Methodology · Statistics 2023-07-31 David Bolin , Alexandre B. Simas , Zhen Xiong

This chapter presents some numerical methods to solve problems in the fractional calculus of variations and fractional optimal control. Although there are plenty of methods available in the literature, we concentrate mainly on approximating…

Optimization and Control · Mathematics 2014-05-19 Shakoor Pooseh , Ricardo Almeida , Delfim F. M. Torres

We consider a conflict-controlled dynamical system described by a nonlinear ordinary fractional differential equation with the Caputo derivative of an order $\alpha \in (0, 1).$ Basing on the finite-difference Gr\"{u}nwald-Letnikov…

Optimization and Control · Mathematics 2019-02-26 Mikhail Gomoyunov

We study the boundary integral operator induced from fractional Laplace equation in a bounded Lipschitz domain. As an application, we study the boundary value problem of a fractional Laplace equation.

Analysis of PDEs · Mathematics 2011-07-07 Tongkeun Chang

We analyze a nonlocal diffusion operator having as special cases the fractional Laplacian and fractional differential operators that arise in several applications. In our analysis, a nonlocal vector calculus is exploited to define a weak…

Analysis of PDEs · Mathematics 2013-03-28 Marta D'Elia , Max Gunzburger

We study discrete versions of fractional integral operators along curves and surfaces. $l^p \to l^q$ estimates are obtained from upper bounds of the number of solutions of associated Diophantine systems. In particular, this relates the…

Classical Analysis and ODEs · Mathematics 2015-05-29 Jongchon Kim

We propose a hybrid framework opPINN: physics-informed neural network (PINN) with operator learning for approximating the solution to the Fokker-Planck-Landau (FPL) equation. The opPINN framework is divided into two steps: Step 1 and Step…

Numerical Analysis · Mathematics 2023-03-22 Jae Yong Lee , Juhi Jang , Hyung Ju Hwang

Some mathematical models of applied problems lead to the need of solving boundary value problems with a fractional power of an elliptic operator. In a number of works, approximations of such a nonlocal operator are constructed on the basis…

Numerical Analysis · Computer Science 2019-05-28 Petr N. Vabishchevich

In this paper approximations of three classes of fractional derivatives (FD) using modified Gauss integration (MGI) and Gauss-Laguerre integration (GLI) are considered. The main solutions of these fractional derivatives depend on inverse of…

Numerical Analysis · Mathematics 2015-03-14 H. Fallahgoul , S. M. Hashemiparast

Operator learning seeks to approximate mappings from input functions to output solutions, particularly in the context of partial differential equations (PDEs). While recent advances such as DeepONet and Fourier Neural Operator (FNO) have…

Machine Learning · Computer Science 2025-05-27 Yile Li , Shandian Zhe