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The efficient solution of discretisations of coupled systems of partial differential equations (PDEs) is at the core of much of numerical simulation. Significant effort has been expended on scalable algorithms to precondition Krylov…

Mathematical Software · Computer Science 2018-02-22 Robert C. Kirby , Lawrence Mitchell

Consider a classical elliptic pseudodifferential operator $P$ on ${\Bbb R}^n$ of order $2a$ ($0<a<1)$ with even symbol. For example, $P=A(x,D)^a$ where $A(x,D)$ is a second-order strongly elliptic differential operator; the fractional…

Analysis of PDEs · Mathematics 2016-04-25 Gerd Grubb

Learning underlying dynamics from data is important and challenging in many real-world scenarios. Incorporating differential equations (DEs) to design continuous networks has drawn much attention recently, however, most prior works make…

Machine Learning · Computer Science 2023-02-03 Yesom Park , Jaemoo Choi , Changyeon Yoon , Chang hoon Song , Myungjoo Kang

The importance of the theory of pseudo-differential operators in the study of non linear integrable systems is point out. Principally, the algebra $\Xi $ of nonlinear (local and nonlocal) differential operators, acting on the ring of…

Mathematical Physics · Physics 2009-12-22 M. B. Sedra

Wave-like partial differential equations occur in many engineering applications. Here the engineering setup is embedded into the Hilbert space framework of functional analysis of modern mathematical physics. The notion wave-like is a…

Mathematical Physics · Physics 2024-05-07 Reinhard Honegger , Michael Lauxmann , Barbara Priwitzer

We propose an operational method for the solution of differential equations involving vector products. The technique we propose is based on the use of the evolution operator, defined in such a way that the wealth of techniques developed…

Mathematical Physics · Physics 2010-09-28 D. Babusci , G. Dattoli , E. Sabia

The standard text book theory of ODEs lacks a general method to solve linear equations having variable coefficients, providing instead a collection of special techniques for particular classes of equations. The present article addresses…

Classical Analysis and ODEs · Mathematics 2025-12-30 Peter C. Gibson

Separable coordinate systems are introduced in the complex and real four-dimensional flat spaces. We use maximal Abelian subgroups to generate coordinate systems with a maximal number of ignorable variables. The results are presented (also…

Mathematical Physics · Physics 2017-08-11 E. G. Kalnins , Z. Thomova , P. Winternitz

The reduction operators, i.e., the operators of nonclassical (conditional) symmetry, of (1+1)-dimensional second order linear parabolic partial differential equations and all the possible reductions of these equations to ordinary…

Analysis of PDEs · Mathematics 2008-06-12 Roman O. Popovych

In this paper we present an $L^p$-theory for the stochastic partial differential equations (SPDEs in abbreciation) driven by L\'e{}vy processes. Existence and uniqueness of solutions in Sobolev spaces are obtained. The coefficients of SPDEs…

Probability · Mathematics 2010-07-21 Zhen-Qing Chen , Kyeong-Hun Kim

We consider a general discrete Sobolev inner product involving the Hahn difference operator, so this includes the well--known difference operators $\mathscr{D}_{q}$ and $\Delta$ and, as a limit case, the derivative operator. The objective…

Classical Analysis and ODEs · Mathematics 2022-08-02 Galina Filipuk , Juan F. Mañas-Mañas , Juan J. Moreno-Balcázar

We consider a two-dimensional integrable Hamiltonian system with a vector and scalar potential in quantum mechanics. Contrary to the case of a pure scalar potential, the existence of a second order integral of motion does not guarantee the…

Mathematical Physics · Physics 2007-05-23 F. Charest , C. Hudon , P. Winternitz

Much recent work has addressed the solution of a family of partial differential equations by computing the inverse operator map between the input and solution space. Toward this end, we incorporate function-valued reproducing kernel Hilbert…

Numerical Analysis · Mathematics 2022-04-05 Kaijun Bao , Xu Qian , Ziyuan Liu , Songhe Song

Computer algebra procedures to manipulate pseudo-differential operators are implemented to perform calculations with integrable models. We use lazy evaluation and streams to represent and operate with pseudo-differential operators. No order…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 Jose Carlos Brunelli

We formulate the functional Bethe ansatz for bosonic (infinite dimensional) representations of the Yang-Baxter algebra. The main deviation from the standard approach consists in a half infinite 'Sklyanin lattice' made of the eigenvalues of…

Mathematical Physics · Physics 2014-11-21 Luigi Amico , Holger Frahm , Andreas Osterloh , Tobias Wirth

A signature independent formalism is created and utilized to determine the general second-order symmetry operators for Dirac's equation on two-dimensional Lorentzian spin manifolds. The formalism is used to characterize the orthonormal…

Mathematical Physics · Physics 2011-06-16 Alberto Carignano , Lorenzo Fatibene , Raymond G. McLenaghan , Giovanni Rastelli

An equation containing a fractional power of an elliptic operator of second order is studied for Dirichlet boundary conditions. Finite difference approximations in space are employed. The proposed numerical algorithm is based on solving an…

Numerical Analysis · Computer Science 2015-05-18 Petr N. Vabishchevich

A formal definition of the graded algebra $\mathcal{R}$ of modular linear differential operators is given and its properties are studied. An algebraic structure of the solutions to modular linear differential equations (MLDEs) is shown. It…

Number Theory · Mathematics 2018-07-20 Fumitoshi Yamashita

The modified biharmonic equation is encountered in a variety of application areas, including streamfunction formulations of the Navier-Stokes equations. We develop a separation of variables representation for this equation in polar…

Numerical Analysis · Mathematics 2017-10-17 Travis Askham

Solving partial differential equations (PDEs) by learning the solution operators has emerged as an attractive alternative to traditional numerical methods. However, implementing such architectures presents two main challenges: flexibility…

Machine Learning · Computer Science 2023-12-19 Seungjun Lee , Taeil Oh
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