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In the theory and practice of inverse problems for partial differential equations (PDEs) much attention is paid to the problem of the identification of coefficients from some additional information. This work deals with the problem of…

Numerical Analysis · Computer Science 2013-04-23 P. N. Vabishchevich , V. I. Vasil'ev

We study the autonomous systems of quadratic differential equations of the form $\dot{x}_i(t)=\mathbf{x}(t)^T \mathbf{A}_i \mathbf{x}(t) + \mathbf{v}_i^T \mathbf{x}(t)$ with $\mathbf{x}(t) = (x_1(t),x_2(t),\dots,x_i(t),\dots)$ which, in…

Dynamical Systems · Mathematics 2023-11-22 Ádám Bácsi , Albert Tihamér Kocsis

We present two approaches to system identification, i.e. the identification of partial differential equations (PDEs) from measurement data. The first is a regression-based Variational System Identification procedure that is advantageous in…

Computational Physics · Physics 2024-03-28 Zhenlin Wang , Bowei Wu , Krishna Garikipati , Xun Huan

We obtain global and local theorems on the existence of invariant manifolds for perturbations of non autonomous linear differential equations assuming a very general form of dichotomic behavior for the linear equation. Besides some new…

Dynamical Systems · Mathematics 2013-10-03 António J. G. Bento , César M. Silva

We consider the Cauchy problem for first order systems. Assuming that the set of the singular points of the characteristic variety is a smooth manifold and the characteristic values are real and semi-simple we introduce a new class which is…

Analysis of PDEs · Mathematics 2020-12-23 Tatsuo Nishitani

Random invariant manifolds are geometric objects useful for understanding complex dynamics under stochastic influences. Under a nonuniform hyperbolicity or a nonuniform exponential dichotomy condition, the existence of random pseudo-stable…

Dynamical Systems · Mathematics 2009-01-06 Tomas Caraballo , Jinqiao Duan , Kening Lu , Bjorn Schmalfuss

We propose the method for obtaining invariants of arbitrary representations of Lie groups that reduces this problem to known problems of linear algebra. The basis of this method is the idea of a special extension of the representation…

Representation Theory · Mathematics 2017-10-24 Oleg L. Kurnyavko , Igor V. Shirokov

In this paper, a family of variable-coefficient fifth-order KdV equations has been considered. By using an infinitesimal method based on the determination of the equivalence group, differential invariants and invariant equations are…

Analysis of PDEs · Mathematics 2024-02-07 María de los Santos Bruzón , Rafael de la Rosa , Rita Tracinà

In the article we discuss the notion of the generalized invariant manifold introduced in our previous study. In the literature the method of the differential constraints is well known as a tool for constructing particular solutions for the…

Exactly Solvable and Integrable Systems · Physics 2021-07-08 I. T. Habibullin , A. R. Khakimova , A. O. Smirnov

We establish that stabilization of a class of linear, hyperbolic partial differential equations (PDEs) with a large (nevertheless finite) number of components, can be achieved via employment of a backstepping-based control law, which is…

Optimization and Control · Mathematics 2024-11-05 Jukka-Pekka Humaloja , Nikolaos Bekiaris-Liberis

The Lie point symmetries and corresponding invariant solutions are obtained for a Gaussian, irrotational, compressible fluid flow. A supersymmetric extension of this model is then formulated through the use of a superspace and superfield…

Mathematical Physics · Physics 2009-11-13 A. M. Grundland , A. J. Hariton

Advanced deep learning-based approaches have been actively applied to forecast the spatiotemporal physical dynamics governed by partial differential equations (PDEs), which acts as a critical procedure in tackling many science and…

Machine Learning · Computer Science 2026-03-03 Siyang Li , Yize Chen , Yan Guo , Ming Huang , Hui Xiong

In this paper we consider generalization of procedure of construction of potential systems for systems of partial differential equations with multidimensional spaces of conservation laws. More precisely, for construction of potential…

Mathematical Physics · Physics 2008-12-17 N. M. Ivanova

The present work proposes a well-balanced finite volume-type numerical method for the solution of non-conservative hyperbolic partial differential equations (PDEs) with source terms. The method is characterized, first, by the use of a…

Numerical Analysis · Mathematics 2026-05-06 Chiara Colombo , Caterina Dalmaso , Lucas O. Müller , Annunziato Siviglia

In this work we present a novel framework for the computation of finite dimensional invariant sets of infinite dimensional dynamical systems. It extends a classical subdivision technique [Dellnitz/Hohmann 1997] for the computation of such…

Dynamical Systems · Mathematics 2018-08-29 Michael Dellnitz , Mirko Hessel-von Molo , Adrian Ziessler

Many processes in science and engineering can be described by partial differential equations (PDEs). Traditionally, PDEs are derived by considering first principles of physics to derive the relations between the involved physical quantities…

Machine Learning · Statistics 2019-03-27 Jens Berg , Kaj Nyström

We consider uniformly strongly elliptic systems of the second order with bounded coefficients. First, sufficient conditions for the invariance of convex bodies obtained for linear systems without zero order term in bounded domains and…

Analysis of PDEs · Mathematics 2014-12-09 Gershon Kresin , Vladimir Maz'ya

In this paper, we propose a procedure for constructing an infinite number of families of solutions of given linear differential equations with partial derivatives with constant coefficients. We use monogenic functions that are defined on…

Complex Variables · Mathematics 2018-11-28 Vitalii Shpakivskyi

In this paper, we study diagonalizable hyperbolic systems in one space dimension. Based on a new gradient entropy estimate, we prove the global existence of a continuous solution, for large and nondecreasing initial data. Moreover, we show…

Mathematical Physics · Physics 2008-12-18 Ahmad El Hajj , Regis Monneau

Physics-informed neural networks have emerged as a prominent new method for solving differential equations. While conceptually straightforward, they often suffer training difficulties that lead to relatively large discretization errors or…

Mathematical Physics · Physics 2024-03-13 Shivam Arora , Alex Bihlo , Francis Valiquette