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The E(xplicit)I(implicit)N(null) method was developed recently to remove numerical instability from PDEs, adding and subtracting an operator $\mathcal{D}$ of arbitrary structure, treating the operator implicitly in one case, and explicitly…

Numerical Analysis · Mathematics 2022-10-19 Laurent Duchemin , Jens Eggers

In this chapter we provide an introduction to fractional dissipative partial differential equations (PDEs) with a focus on trying to understand their dynamics. The class of PDEs we focus on are reaction-diffusion equations but we also…

Learning the evolutionary dynamics of Partial Differential Equations (PDEs) is critical in understanding dynamic systems, yet current methods insufficiently learn their representations. This is largely due to the multi-scale nature of the…

Machine Learning · Computer Science 2024-10-16 Aoming Liang , Zhaoyang Mu , Pengxiao Lin , Cong Wang , Mingming Ge , Ling Shao , Dixia Fan , Hao Tang

The study of symmetries of partial differential equations (PDEs) has been traditionally treated as a geometrical problem. Although geometrical methods have been proven effective with regard to finding infinitesimal symmetry transformations,…

Analysis of PDEs · Mathematics 2025-11-03 C. J. Papachristou

Bistability is a key property of many systems arising in the nonlinear sciences. For example, it appears in many partial differential equations (PDEs). For scalar bistable reaction-diffusions PDEs, the bistable case even has take on…

Spectral Theory · Mathematics 2023-01-02 Paolo Bernuzzi , Christian Kühn

Stochastic partial differential equations (SPDEs) represent a very active research field with numerous recent developments and breakthrough results. There are several well-established approaches and methods used to construct solutions for…

Probability · Mathematics 2019-08-27 Christian Kuehn , Alexandra Neamtu

Mixed-dimensional partial differential equations (PDEs) are characterized by coupled operators defined on domains of varying dimensions and pose significant computational challenges due to their inherent ill-conditioning. Moreover, the…

Numerical Analysis · Mathematics 2025-05-14 Nunzio Dimola , Nicola Rares Franco , Paolo Zunino

Parabolic partial differential equations (PDEs) appear in many disciplines to model the evolution of various mathematical objects, such as probability flows, value functions in control theory, and derivative prices in finance. It is often…

Machine Learning · Computer Science 2024-07-18 Xingzi Xu , Ali Hasan , Jie Ding , Vahid Tarokh

We present a new solver for coupled nonlinear elliptic partial differential equations (PDEs). The solver is based on pseudo-spectral collocation with domain decomposition and can handle one- to three-dimensional problems. It has three…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Harald P. Pfeiffer , Lawrence E. Kidder , Mark A. Scheel , Saul A. Teukolsky

In this paper, we develop a comprehensive mathematical toolbox for the construction and spectral stability analysis of stationary multiple front and pulse solutions to general semilinear evolution problems on the real line with spatially…

Analysis of PDEs · Mathematics 2025-02-05 Lukas Bengel , Björn de Rijk

Recent biological evidence suggests the presence of a two-phase ageing process in several species. We introduce a system of two age-structured partial differential equations (PDE) representing two phases of ageing of a wild population. The…

Analysis of PDEs · Mathematics 2026-03-24 Luce Breuil

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

In this paper, the stability of fractional differential equations (FDEs) with unknown parameters is studied. FDEs bring many advantages to model the physical systems in the nature or man-made systems in the industry. Because this…

Systems and Control · Computer Science 2020-08-13 Mehmet Emir Koksal

We consider constrained bilinear optimal control of second-order linear evolution partial differential equations (PDEs) with a reaction term on the half line, where control arises as a time-dependent reaction coefficient and constraints are…

Computational Physics · Physics 2025-11-20 Zhexian Li , Felipe de Barros , Ketan Savla

In this paper, we present a general methodology for investigating the linear stability of localized solutions in PDEs and nonlocal equations on $\mathbb{R}^m$. More specifically, we control the spectrum of the Jacobian…

Analysis of PDEs · Mathematics 2025-05-07 Matthieu Cadiot

Dynamical systems that are subject to continuous uncertain fluctuations can be modelled using Stochastic Differential Equations (SDEs). Controlling such system results in solving path constrained SDEs. Broadly, these problems fall under the…

Optimization and Control · Mathematics 2023-06-16 Sumit Suthar , Soumyendu Raha

Partial Differential Equations (PDEs) are central to science and engineering. Since solving them is computationally expensive, a lot of effort has been put into approximating their solution operator via both traditional and recently…

Machine Learning · Computer Science 2025-02-14 Alessandro Longhi , Danny Lathouwers , Zoltán Perkó

This paper addresses the robust stability of a boundary controlled system coupling two partial differential equations (PDEs), namely beam and string equations, in the presence of boundary and in-domain disturbances under the framework of…

Analysis of PDEs · Mathematics 2018-11-19 Jun Zheng , Hugo Lhachemi , Guchuan Zhu , David Saussi

Spatial reaction-diffusion models have been employed to describe many emergent phenomena in biological systems. The modelling technique most commonly adopted in the literature implements systems of partial differential equations (PDEs),…

Quantitative Methods · Quantitative Biology 2015-10-05 Christian A. Yates , Mark B. Flegg

Partial Differential Equations (PDEs) with high dimensionality are commonly encountered in computational physics and engineering. However, finding solutions for these PDEs can be computationally expensive, making model-order reduction…

Machine Learning · Statistics 2023-03-07 Sebastian Kaltenbach , Phaedon-Stelios Koutsourelakis , Petros Koumoutsakos