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In this work, we introduce new second-order schemes for one- and two-dimensional hyperbolic systems of conservation laws. Following an approach recently proposed in [{\sc R. Abgrall}, Commun. Appl. Math. Comput., 5 (2023), pp. 370--402], we…

Numerical Analysis · Mathematics 2025-12-24 Rémi Abgrall , Alina Chertock , Alexander Kurganov , Lorenzo Micalizzi

We consider the discretization in time of a system of parabolic stochastic partial differential equations with slow and fast components; the fast equation is driven by an additive space-time white noise. The numerical method is inspired by…

Numerical Analysis · Mathematics 2012-02-14 Charles-Edouard Bréhier

An adaptive direct collocation method is developed for solving optimal control problems constrained by parabolic partial differential equations. The partial differential equation is first reformulated in a variational setting, where the…

Optimization and Control · Mathematics 2026-03-18 Alexander M. Davies , Sara Pollock , Miriam E. Dennis , Anil V. Rao

Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional…

Optimization and Control · Mathematics 2020-01-06 Joseph Hart , Bart van Bloemen Waanders , Roland Herzog

In this work we propose a new, arbitrary order space-time finite element discretisation for Hamiltonian PDEs in multisymplectic formulation. We show that the new method which is obtained by using both continuous and discontinuous…

Numerical Analysis · Mathematics 2021-08-18 Elena Celledoni , James Jackaman

We propose a time-adaptive predictor/multi-corrector method to solve hyperbolic partial differential equations, based on the generalized-$\alpha$ scheme that provides user-control on the numerical dissipation and second-order accuracy in…

Numerical Analysis · Mathematics 2022-10-11 Nicolas A. Labanda , Pouria Behnoudfar , Victor M. Calo

Using purely probabilistic methods, we prove the existence and the uniqueness of solutions fora system of coupled forward-backward stochastic differential equations (FBSDEs) with measurable, possibly discontinuous coefficients. As a…

Probability · Mathematics 2021-10-12 Kihun Nam , Yunxi Xu

This study proposes a novel spatial discretization procedure for the compressible Euler equations which guarantees entropy conservation at a discrete level when an arbitrary equation of state is assumed. The proposed method, based on a…

Fluid Dynamics · Physics 2025-09-24 Alessandro Aiello , Carlo De Michele , Gennaro Coppola

This paper is about learning the parameter-to-solution map for systems of partial differential equations (PDEs) that depend on a potentially large number of parameters covering all PDE types for which a stable variational formulation (SVF)…

Numerical Analysis · Mathematics 2024-05-31 Markus Bachmayr , Wolfgang Dahmen , Mathias Oster

Semilinear hyperbolic stochastic partial differential equations (SPDEs) find widespread applications in the natural and engineering sciences. However, the traditional Gaussian setting may prove too restrictive, as phenomena in mathematical…

Numerical Analysis · Mathematics 2023-07-04 Andrea Barth , Andreas Stein

In this paper, we develop bound-preserving (BP) finite-volume schemes for hyperbolic conservation laws on adaptive moving meshes. For scalar conservative laws, we rewrite the conventional high-order discretization as a convex combination of…

Numerical Analysis · Mathematics 2026-02-16 Yaguang Gu , Guanghui Hu , Tao Tang

The Fokker-Planck equations (FPEs) for stochastic systems driven by additive symmetric $\alpha$-stable noises may not adequately describe the time evolution for the probability densities of solution paths in some practical applications,…

Dynamical Systems · Mathematics 2020-03-11 Yanjie Zhang , Xiao Wang , Qiao Huang , Jinqiao Duan , Tingting Li

Monotone finite difference methods provide stable convergent discretizations of a class of degenerate elliptic and parabolic Partial Differential Equations (PDEs). These methods are best suited to regular rectangular grids, which leads to…

Numerical Analysis · Mathematics 2015-11-19 Adam M. Oberman , Ian Zwiers

We construct a finite element discretization and time-stepping scheme for the incompressible Euler equations with variable density that exactly preserves total mass, total squared density, total energy, and pointwise incompressibility. The…

Numerical Analysis · Mathematics 2020-04-22 Evan S. Gawlik , François Gay-Balmaz

We analyze stochastic partial differential equations (SPDEs) with quadratic nonlinearities close to a change of stability. To this aim we compute finite-time Lyapunov exponents (FTLEs), observing a change of sign based on the interplay…

Probability · Mathematics 2026-02-11 Alexandra Blessing , Dirk Blömker

Modeling complex spatiotemporal dynamical systems, such as the reaction-diffusion processes, have largely relied on partial differential equations (PDEs). However, due to insufficient prior knowledge on some under-explored dynamical…

Machine Learning · Computer Science 2023-05-23 Chengping Rao , Pu Ren , Qi Wang , Oral Buyukozturk , Hao Sun , Yang Liu

We propose a modification of the standard linear implicit Euler integrator for the weak approximation of parabolic semilinear stochastic PDEs driven by additive space-time white noise. The new method can easily be combined with a finite…

Numerical Analysis · Mathematics 2022-03-22 Charles-Edouard Bréhier

We propose a numerical method to solve general hyperbolic systems in any space dimension using forward Euler time stepping and continuous finite elements on non-uniform grids. The properties of the method are based on the introduction of an…

Numerical Analysis · Mathematics 2015-09-25 Jean-Luc Guermond , Bojan Popov

Many systems in physics, engineering, and biology exhibit multiscale stochastic dynamics, where low-dimensional slow variables evolve under the influence of high-dimensional fast processes. In practice, observations are often limited to a…

Machine Learning · Statistics 2026-05-12 Anan Saha , Arnab Ganguly

This paper aims to investigate the numerical approximation of semilinear non-autonomous stochastic partial differential equations (SPDEs) driven by multiplicative or additive noise. Such equations are more realistic than autonomous SPDEs…

Numerical Analysis · Mathematics 2020-11-18 Jean Daniel Mukam , Antoine Tambue
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