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We introduce a discontinuous Galerkin method for the mixed formulation of the elasticity eigenproblem with reduced symmetry. The analysis of the resulting discrete eigenproblem does not fit in the standard spectral approximation framework…

Numerical Analysis · Mathematics 2018-01-29 Felipe Lepe , Salim Meddahi , David Mora , Rodolfo Rodríguez

In present paper we propose seemingly new method for finding solutions of some types of nonlinear PDEs in closed form. The method is based on decomposition of nonlinear operators on sequence of operators of lower orders. It is shown that…

Mathematical Physics · Physics 2007-05-23 Yu. N. Kosovtsov

Nonlinear partial differential equations (PDEs) are used to model dynamical processes in a large number of scientific fields, ranging from finance to biology. In many applications standard local models are not sufficient to accurately…

Numerical Analysis · Mathematics 2022-05-10 Victor Boussange , Sebastian Becker , Arnulf Jentzen , Benno Kuckuck , Loïc Pellissier

In this article we study the well-posedness (uniqueness and existence of solutions) of nonlinear elliptic Partial Differential Equations (PDEs) on a finite graph. These results are obtained using the discrete comparison principle and…

Analysis of PDEs · Mathematics 2013-03-01 Juan J. Manfredi , Adam M. Oberman , Alex P. Svirodov

Explicit, unconditionally stable, high-order schemes for the approximation of some first- andsecond-order linear, time-dependent partial differential equations (PDEs) are proposed.The schemes are based on a weak formulation of a…

Numerical Analysis · Mathematics 2017-11-15 Olivier Bokanowski , Giorevinus Simarmata

A partial differential equation (PDE) was developed to describe time-dependent ligand-receptor interactions for applications in biosensing using field effect transistors (FET). The model describes biochemical interactions at the sensor…

Analysis of PDEs · Mathematics 2017-10-20 Ryan M. Evans , Arvind Balijepalli , Anthony J. Kearsley

The discovery of partial differential equations (PDEs) is a challenging task that involves both theoretical and empirical methods. Machine learning approaches have been developed and used to solve this problem; however, it is important to…

Machine Learning · Statistics 2023-06-09 Kalpesh More , Tapas Tripura , Rajdip Nayek , Souvik Chakraborty

A discontinuous Galerkin (dG) method for the numerical solution of initial/boundary value multi-compartment partial differential equation (PDE) models, interconnected with interface conditions, is presented and analysed. The study of…

Numerical Analysis · Mathematics 2013-04-16 Andrea Cangiani , Emmanuil H. Georgoulis , Max Jensen

In this work, we investigate the propagation of electromagnetic waves in the Cole-Cole dispersive medium by using the discontinuous Galerkin (DG) method to solve the coupled time-domain Maxwell's equations and polarization equation. We…

Numerical Analysis · Mathematics 2022-08-25 Jiangming Xie , Maojun Li , Miao-Jung Yvonne Ou

We prove the existence of fast traveling pulse solutions in excitable media with non-local coupling. Existence results had been known, until now, in the case of local, diffusive coupling and in the case of a discrete medium, with…

Analysis of PDEs · Mathematics 2013-11-27 Gregory Faye , Arnd Scheel

Partial differential equation (PDE) models with multiple temporal/spatial scales are prevalent in several disciplines such as physics, engineering, and many others. These models are of great practical importance but notoriously difficult to…

Numerical Analysis · Mathematics 2023-04-17 Junpeng Hu , Shi Jin , Lei Zhang

We develop and study a time-space discrete discontinuous Galerkin finite elements method to approximate the solution of one-dimensional nonlinear wave equations. We show that the numerical scheme is stable if a nonuniform time mesh is…

Analysis of PDEs · Mathematics 2021-04-07 Asma Azaiez , Mondher Benjemaa , Aida Jrajria , Hatem Zaag

The Legendre spectral Galerkin method of self-adjoint second order elliptic equations usually results in a linear system with a dense and ill-conditioned coefficient matrix. In this paper, the linear system is solved by a preconditioned…

Numerical Analysis · Mathematics 2020-04-30 Xuhao Diao , Jun Hu , Suna Ma

We apply the Local Discontinuous Galerkin discretisation to flow equations of the O(N)-model in the Local Potential Approximation. The improved stability is directly observed by solving the flow equation for various $N$ and space-time…

High Energy Physics - Theory · Physics 2022-08-17 Friederike Ihssen , Jan M. Pawlowski , Franz R. Sattler , Nicolas Wink

This work proposes stochastic partial differential equations (SPDEs) as a practical tool to replicate clustering effects of more detailed particle-based dynamics. Inspired by membrane-mediated receptor dynamics on cell surfaces, we…

Quantitative Methods · Quantitative Biology 2025-01-22 Nathalie Wehlitz , Mohsen Sadeghi , Alberto Montefusco , Christof Schütte , Grigorios A. Pavliotis , Stefanie Winkelmann

The aim of this paper is to apply a high-order discontinuous-in-time scheme to second-order hyperbolic partial differential equations (PDEs). We first discretize the PDEs in time while keeping the spatial differential operators…

Numerical Analysis · Mathematics 2021-11-30 Aili Shao

In this paper, we propose a fully discrete mixed finite element method for solving the time-dependent Ginzburg--Landau equations, and prove the convergence of the finite element solutions in general curved polyhedra, possibly nonconvex and…

Numerical Analysis · Mathematics 2016-05-06 Buyang Li

Simulating electromagnetic fields across broad frequency ranges is challenging due to numerical instabilities at low frequencies. This work extends a stabilized two-step formulation of Maxwell's equations to the time-domain. Using a…

Numerical Analysis · Mathematics 2025-10-17 Leon Herles , Mario Mally , Jörg Ostrowski , Sebastian Schöps , Melina Merkel

In this paper we establish a connection between non-convex optimization methods for training deep neural networks and nonlinear partial differential equations (PDEs). Relaxation techniques arising in statistical physics which have already…

Machine Learning · Computer Science 2017-06-05 Pratik Chaudhari , Adam Oberman , Stanley Osher , Stefano Soatto , Guillaume Carlier

We consider the discretization of a class of nonlinear parabolic equations by discontinuous Galerkin time-stepping methods and establish a priori as well as conditional a posteriori error estimates. Our approach is motivated by the error…

Numerical Analysis · Mathematics 2024-12-12 Georgios Akrivis , Stig Larsson
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