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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

We consider a class of semilinear stochastic evolution equations driven by an additive cylindrical stable noise.We investigate structural properties of the solutions like Markov, irreducibility, stochastic continuity, Feller and strong…

Analysis of PDEs · Mathematics 2011-10-06 Enrico Priola , Jerzy Zabczyk

Nonlinear (systems of) ordinary differential equations (ODEs) are common tools in the analysis of complex one-dimensional dynamic systems. In this paper we propose a smoothing approach regularized by a quasilinearized ODE-based penalty in…

Methodology · Statistics 2014-04-30 Gianluca Frasso , Jonathan Jaeger , Philippe Lambert

We consider a class of parabolic semi-linear stochastic partial differential equations driven by space-time white noise on a compact space interval. Our aim is to obtain precise asymptotics of the transition times between metastable states.…

Probability · Mathematics 2012-01-24 Florent Barret

This paper aims to develop and analyze a numerical scheme for solving the backward problem of semilinear subdiffusion equations. We establish the existence, uniqueness, and conditional stability of the solution to the inverse problem by…

Numerical Analysis · Mathematics 2025-05-07 Xu Wu , Jiang Yang , Zhi Zhou

In this article a stabilizing feedback control is computed for a semilinear parabolic partial differential equation utilizing a nonlinear model predictive (NMPC) method. In each level of the NMPC algorithm the finite time horizon open loop…

Optimization and Control · Mathematics 2014-09-30 Alessandro Alla , Stefan Volkwein

Semi-Lagrangian methods are numerical methods designed to find approximate solutions to particular time-dependent partial differential equations (PDEs) that describe the advection process. We propose semi-Lagrangian one-step methods for…

Numerical Analysis · Mathematics 2017-03-07 Nikolai D. Lipscomb , Daniel X. Guo

A comprehensive convergence and stability analysis of some probabilistic numerical methods designed to solve Cauchy-type inverse problems is performed in this study. Such inverse problems aim at solving an elliptic partial differential…

Numerical Analysis · Mathematics 2025-08-12 Iulian Cîmpean , Andreea Grecu , Liviu Marin

Whether integrable, partially integrable or nonintegrable, nonlinear partial differential equations (PDEs) can be handled from scratch with essentially the same toolbox, when one looks for analytic solutions in closed form. The basic tool…

Exactly Solvable and Integrable Systems · Physics 2017-10-16 Robert Conte

Coupled partial differential equations defined on domains with different dimensionality are usually called mixed dimensional PDEs. We address mixed dimensional PDEs on three-dimensional (3D) and one-dimensional domains, giving rise to a…

Numerical Analysis · Mathematics 2020-04-07 Miroslav Kuchta , Federica Laurino , Kent-Andre Mardal , Paolo Zunino

We provide a self-contained analysis, based entirely on pde methods, of the exponentially long time behavior of solutions to linear uniformly parabolic equations which are small perturbations of a transport equation with vector field having…

Analysis of PDEs · Mathematics 2020-04-21 Hitoshi Ishii , Panagiotis E. Souganidis

We present strongly convergent explicit and semi-implicit adaptive numerical schemes for systems of stiff stochastic differential equations (SDEs) where both the drift and diffusion are non-globally Lipschitz continuous. This stiffness may…

Numerical Analysis · Mathematics 2021-06-02 Cónall Kelly , Gabriel Lord

This paper presents an alternative approach for the computation of trajectory segments on slow manifolds of saddle type. This approach is based on iterative methods rather than collocation-type methods. Compared to collocation methods, that…

Dynamical Systems · Mathematics 2015-05-07 Kristian Uldall Kristiansen

Recent applications (e.g. active gels and self-assembly of elastic sheets) motivate the need to efficiently simulate the dynamics of thin elastic sheets. We present semi-implicit time stepping algorithms to improve the time step constraints…

Computational Physics · Physics 2019-10-23 Silas Alben , Alex A. Gorodetsky , Donghak Kim , Robert D. Deegan

In this paper we develop an adaptive procedure for the numerical solution of general, semilinear elliptic problems with possible singular perturbations. Our approach combines both a prediction-type adaptive Newton method and an adaptive…

Numerical Analysis · Mathematics 2014-08-27 Mario Amrein , Thomas P. Wihler

Parabolic partial differential equations (PDEs) and backward stochastic differential equations (BSDEs) are key ingredients in a number of models in physics and financial engineering. In particular, parabolic PDEs and BSDEs are fundamental…

Numerical Analysis · Mathematics 2020-11-25 Weinan E , Martin Hutzenthaler , Arnulf Jentzen , Thomas Kruse

We introduce a novel numerical method to integrate partial differential equations representing the Hamiltonian dynamics of field theories. It is a multi-symplectic integrator that locally conserves the stress-energy tensor with an excellent…

Numerical Analysis · Mathematics 2017-02-23 Hugo Ricateau , Leticia F. Cugliandolo

In this paper, we prove that there exists a unique solution to the Dirichlet boundary value problem for a general class of semilinear second order elliptic partial differential equations. Our approach is probabilistic. The theory of…

Probability · Mathematics 2012-11-19 Tusheng Zhang

This paper deals with the existence of solutions for an elliptic system of partial differential equations. The solution method is based on the sub- and super-solutions approach. An application to a stochastic control problem is presented.…

Analysis of PDEs · Mathematics 2020-01-01 Dragos-Patru Covei , Traian A. Pirvu

In this paper we introduce a numerical method for nonlinear parabolic PDEs that combines operator splitting with deep learning. It divides the PDE approximation problem into a sequence of separate learning problems. Since the computational…

Numerical Analysis · Mathematics 2021-10-12 Christian Beck , Sebastian Becker , Patrick Cheridito , Arnulf Jentzen , Ariel Neufeld