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Systems of two ordinary and partial differential equations (ODEs and PDEs) had been obtained from a scalar complex ODE by splitting it into its real and imaginary parts. The procedure was also carried out to obtain a four dimensional system…

Classical Analysis and ODEs · Mathematics 2011-08-29 F M Mahomed , Asghar Qadir

Partial differential equations (PDEs) are at the heart of many mathematical and scientific advances. While great progress has been made on the theory of PDEs of standard types during the last eight decades, the analysis of nonlinear PDEs of…

Analysis of PDEs · Mathematics 2022-08-16 Gui-Qiang G. Chen

Neural operators have emerged as promising surrogate models for solving partial differential equations (PDEs), but struggle to generalise beyond training distributions and are often constrained to a fixed temporal discretisation. This work…

Partial differential equations (PDEs) are among the most universal and parsimonious descriptions of natural physical laws, capturing a rich variety of phenomenology and multi-scale physics in a compact and symbolic representation. This…

Machine Learning · Computer Science 2023-03-31 Steven L. Brunton , J. Nathan Kutz

This article is an exhaustive revision of concepts and formulas related to quaternions and rotations in 3D space, and their proper use in estimation engines such as the error-state Kalman filter. The paper includes an in-depth study of the…

Robotics · Computer Science 2017-11-08 Joan Solà

We review some surprising links which have been discovered in the last few years between the theory of certain ordinary differential equations, and particular integrable lattice models and quantum field theories in two dimensions. An…

High Energy Physics - Theory · Physics 2007-05-23 P. Dorey , C. Dunning , A. Millican-Slater , R. Tateo

We present a lightweighted neural PDE representation to discover the hidden structure and predict the solution of different nonlinear PDEs. Our key idea is to leverage the prior of ``translational similarity'' of numerical PDE differential…

Machine Learning · Computer Science 2023-03-14 Ziqian Wu , Xingzhe He , Yijun Li , Cheng Yang , Rui Liu , Shiying Xiong , Bo Zhu

Quantum computers have the potential to efficiently solve a system of nonlinear ordinary differential equations (ODEs), which play a crucial role in various industries and scientific fields. However, it remains unclear which system of…

Quantum Physics · Physics 2025-04-07 Yu Tanaka , Keisuke Fujii

In this paper, we consider the non-Hermitian quaternion linear systems arising from color image restoration and three-dimensional signal filtering problems. For exploring to solve such systems, we present two innovative structure-preserving…

Numerical Analysis · Mathematics 2026-05-19 Baohua Huang , Tao Li , Wen Li

We represent a version of multidimensional quasilinear partial differential equation (PDE) together with large manifold of particular solutions given in an integral form. The dimensionality of constructed PDE can be arbitrary. We call it…

Exactly Solvable and Integrable Systems · Physics 2015-06-18 A. I. Zenchuk

Due to the existence of incompatible observables, the propositional calculus of a quantum system does not form a Boolean algebra but an orthomodular lattice. Such lattice can be realised as a lattice of subspaces on a real, complex or…

Functional Analysis · Mathematics 2017-09-22 Jonathan Gantner

This paper presents a novel approach for numerical solution of a class of fourth order time fractional partial differential equations (PDE's). The finite difference formulation has been used for temporal discretization, whereas, the space…

Numerical Analysis · Mathematics 2018-09-18 Muhammad Abbas

A class of fourth--order neutral type difference equations with quasidifferences and deviating arguments is considered. Our approach is based on studying the considered equation as a system of a four--dimensional difference system. The…

Dynamical Systems · Mathematics 2014-04-01 Robert Jankowski , Ewa Schmeidel , Joanna Zonenberg

Partial Differential Equation (PDE)-constrained optimization problems often take the form of an optimization of an objective function given as a sum of loss terms. Each function or gradient evaluation requires one or more PDE solves, which…

Optimization and Control · Mathematics 2026-03-10 Cash Cherry , Samy Wu Fung , Luis Tenorio , Ebru Bozdağ

Many nonlinear PDEs have singular or oscillatory solutions or may exhibit physical instabilities or uncertainties. This requires a suitable concept of physically relevant generalized solutions. Dissipative measure-valued solutions have been…

Quantum Physics · Physics 2026-04-15 Shi Jin , Nana Liu , Maria Lukacova-Medvidova , Yuhuan Yuan

Fractional differential equations (FDEs) are an extension of the theory of fractional calculus. However, due to the difficulty in finding analytical solutions, there have not been extensive applications of FDEs until recent decades. With…

Numerical Analysis · Mathematics 2020-07-20 Nirupama Bhattacharya , Gabriel A. Silva

The purpose of this contribution is to provide an introduction for a general physics audience to the recent results of Emile Grgin that unifies quantum mechanics and relativity into the same mathematical structure. This structure is the…

Quantum Physics · Physics 2012-04-10 Florin Moldoveanu

The subject of this thesis is the rigorous construction of QFT models with nontrivial interaction. Two different approaches in the framework of AQFT are discussed. On the one hand, an inverse scattering problem is considered. A given…

Mathematical Physics · Physics 2015-03-04 Sabina Alazzawi

The paper develops the method for construction of families of particular solutions to some classes of nonlinear Partial Differential Equations (PDE). Method is based on the specific link between algebraic matrix equations and PDE.…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. I. Zenchuk

Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with some representative datasets. Recently, an augmented framework has been…

Machine Learning · Computer Science 2021-02-23 Qunxi Zhu , Yao Guo , Wei Lin