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A full Lie point symmetry analysis of rational difference equations is performed. Non-trivial symmetries are derived and exact solutions using these symmetries are obtained.

Dynamical Systems · Mathematics 2019-11-11 M. Folly-Gbetoula , N. Mnguni , AH Kara

We analyze a class of nonlinear partial differential equations (PDEs) defined on $\mathbb{R}^d \times \mathcal{P}_2(\mathbb{R}^d),$ where $\mathcal{P}_2(\mathbb{R}^d)$ is the Wasserstein space of probability measures on $\mathbb{R}^d$ with…

Probability · Mathematics 2015-04-23 Jean-François Chassagneux , Dan Crisan , François Delarue

Classical Lie group theory provides a universal tool for calculating symmetry groups for systems of differential equations. However Lie's method is not as much effective in the case of integral or integro-differential equations as well as…

Mathematical Physics · Physics 2007-05-23 N. H. Ibragimov , V. F. Kovalev , V. V. Pustovalov

For a system of partial differential equations admitting point, contact, or higher symmetries, the framework of invariant reduction systematically computes how invariant geometric structures, such as conservation laws, presymplectic…

Exactly Solvable and Integrable Systems · Physics 2026-03-16 Kostya Druzhkov , Alexei Cheviakov

In this paper, we develop an ensemble-based time-stepping algorithm to efficiently find numerical solutions to a group of linear, second-order parabolic partial differential equations (PDEs). Particularly, the PDE models in the group could…

Numerical Analysis · Mathematics 2017-10-18 Yan Luo , Zhu Wang

This paper develops a new class of Rosenbrock-type integrators based on a Krylov space solution of the linear systems. The new family, called Rosenbrock-Krylov (Rosenbrock-K), is well suited for solving large scale systems of ODEs or…

Numerical Analysis · Mathematics 2015-01-30 Paul Tranquilli , Adrian Sandu

Elliptic partial differential equations (PDEs) arise in many areas of computational sciences such as computational fluid dynamics, biophysics, engineering, geophysics and more. They are difficult to solve due to their global nature and…

Computational Engineering, Finance, and Science · Computer Science 2022-05-09 Damyn M Chipman

Perturbative renormalization group theory is developed as a unified tool for global asymptotic analysis. With numerous examples, we illustrate its application to ordinary differential equation problems involving multiple scales, boundary…

High Energy Physics - Theory · Physics 2008-11-26 Lin-Yuan Chen , Nigel Goldenfeld , Y. Oono

We revisit the general framework introduced by Fazylab et al. (SIAM J. Optim. 28, 2018) to construct Lyapunov functions for optimization algorithms in discrete and continuous time. For smooth, strongly convex objective functions, we relax…

Optimization and Control · Mathematics 2024-05-21 Paul Dobson , Jesus Maria Sanz-Serna , Konstantinos Zygalakis

Enhancing and essentially generalizing previous results on a class of (1+1)-dimensional nonlinear wave and elliptic equations, we apply several new techniques to classify admissible point transformations within this class up to the…

Mathematical Physics · Physics 2020-07-07 Olena O. Vaneeva , Alexander Bihlo , Roman O. Popovych

The intrinsic geometric properties of generalized Darboux-Manakov-Zakharov systems of semilinear partial differential equations \label{GDMZabstract} \frac{\partial^2 u}{\partial x_i\partial x_j}=f_{ij}\Big(x_k,u,\frac{\partial u}{\partial…

Differential Geometry · Mathematics 2010-02-08 Peter J. Vassiliou

Symmetry groups of PDEs allow to transform solutions continuously into other solutions. In this paper, we use this property for the observability analysis of nonlinear PDEs with input and output. Based on a differential-geometric…

Optimization and Control · Mathematics 2018-07-19 Bernd Kolar , Hubert Rams , Markus Schöberl

symmetry, group classification, differential invariants, Lie-classical method,infinitesimal criterion method, RDC equation, KPP equation, similarity solutions.

Analysis of PDEs · Mathematics 2018-08-01 Mehdi Nadjafikhah , Saeed Dodangeh

This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from…

Numerical Analysis · Mathematics 2024-10-17 Kiefer Green , Harbir Antil

The paper proposes an algorithm which could identify a general class of pdes describing dynamical systems with similar symmetries. The way that will be followed starts from a given group of symmetries, the determination of the invariants…

Mathematical Physics · Physics 2015-06-03 Rodica Cimpoiasu , Radu Constantinescu

We represent an algorithm allowing one to construct new classes of partially integrable multidimensional nonlinear partial differential equations (PDEs) starting with the special type of solutions to the (1+1)-dimensional hierarchy of…

Exactly Solvable and Integrable Systems · Physics 2015-05-13 A. I. Zenchuk

Linear partial differential equations (PDEs) are an important, widely applied class of mechanistic models, describing physical processes such as heat transfer, electromagnetism, and wave propagation. In practice, specialized numerical…

Machine Learning · Computer Science 2024-04-30 Marvin Pförtner , Ingo Steinwart , Philipp Hennig , Jonathan Wenger

A new singular perturbation method based on the Lie symmetry group is presented to a system of difference equations. This method yields consistent derivation of a renormalization group equation which gives an asymptotic solution of the…

Chaotic Dynamics · Physics 2009-11-13 Masatomo Iwasa , Kazuhiro Nozaki

Based on an original classification of differential equations by types of regular Lie group actions, we offer a systematic procedure for describing partial differential equations with prescribed symmetry groups. Using a new powerful…

Mathematical Physics · Physics 2021-01-01 Alexey A. Magazev , Igor V. Shirokov

We present a deep learning algorithm for the numerical solution of parametric families of high-dimensional linear Kolmogorov partial differential equations (PDEs). Our method is based on reformulating the numerical approximation of a whole…

Machine Learning · Computer Science 2021-05-11 Julius Berner , Markus Dablander , Philipp Grohs