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We present a novel multilevel Monte Carlo approach for estimating quantities of interest for stochastic partial differential equations (SPDEs). Drawing inspiration from [Giles and Szpruch: Antithetic multilevel Monte Carlo estimation for…

Numerical Analysis · Mathematics 2025-04-15 Abdul-Lateef Haji-Ali , Andreas Stein

We present an abstract concept for the error analysis of numerical schemes for semilinear stochastic partial differential equations (SPDEs) and demonstrate its usefulness by proving the strong convergence of a Milstein-Galerkin finite…

Numerical Analysis · Mathematics 2014-11-26 Raphael Kruse

We present several methods, which utilize symplectic integration techniques based on two and three part operator splitting, for numerically solving the equations of motion of the disordered, discrete nonlinear Schr\"odinger (DDNLS)…

Computational Physics · Physics 2016-04-11 Enrico Gerlach , Jan Meichsner , Charalampos Skokos

We consider Hamiltonian PDEs that can be split into a linear unbounded operator and a regular non linear part. We consider abstract splitting methods associated with this decomposition where no discretization in space is made. We prove a…

Numerical Analysis · Mathematics 2008-11-26 Erwan Faou , Benoit Grebert , Eric Paturel

In [8], some exact splittings are proposed for inhomogeneous quadratic differential equations including, for example, transport equations, kinetic equations, and Schr{\"o}dinger type equations with a rotation term. In this work, these exact…

Numerical Analysis · Mathematics 2020-01-01 Joackim Bernier , Nicolas Crouseilles , Yingzhe Li

We address parameter estimation in second-order stochastic differential equations (SDEs), which are prevalent in physics, biology, and ecology. The second-order SDE is converted to a first-order system by introducing an auxiliary velocity…

Methodology · Statistics 2025-04-17 Predrag Pilipovic , Adeline Samson , Susanne Ditlevsen

Construction of splitting-step methods and properties of related non-negativity and boundary preserving numerical algorithms for solving stochastic differential equations (SDEs) of Ito-type are discussed. We present convergence proofs for a…

Numerical Analysis · Mathematics 2007-05-23 Esteban Moro , Henri Schurz

In this article, we propose a Milstein finite difference scheme for a stochastic partial differential equation (SPDE) describing a large particle system. We show, by means of Fourier analysis, that the discretisation on an unbounded domain…

Numerical Analysis · Mathematics 2012-04-09 Michael B. Giles , Christoph Reisinger

In this paper, we examine the problem of sampling from log-concave distributions with (possibly) superlinear gradient growth under kinetic (underdamped) Langevin algorithms. Using a carefully tailored taming scheme, we propose two novel…

Probability · Mathematics 2025-12-10 Iosif Lytras , Panayotis Mertikopoulos

In this paper we are interested in a quasi-linear hyperbolic stochastic differential equation (HSPDE) when the vector field is merely bounded and measurable. Although the deterministic counterpart of such equation may be ill-posed (in the…

Probability · Mathematics 2025-09-08 Antoine-Marie Bogso , Moustapha Dieye , Olivier Menoukeu Pamen , Frank Proske

A new class of semi-implicit numerical schemes for linear advection equation on Cartesian grids is derived that is inspired by so-called $\kappa$-schemes used with fully explicit discretizations for this type of problems. Opposite to fully…

Numerical Analysis · Mathematics 2016-11-15 Peter Frolkovič , Karol Mikula

In this paper, we report about recent findings in the numerical solution of Hamiltonian Partial Differential Equations (PDEs), by using energy-conserving line integral methods in the Hamiltonian Boundary Value Methods (HBVMs) class. In…

Numerical Analysis · Mathematics 2019-03-19 Luigi Brugnano , Gianluca Frasca-Caccia , Felice Iavernaro

In the paper, we propose a higher-order geometry-preserving numerical method for stochastic differential equations (SDEs) evolving on the Lie groups SO(n) and SE(n). Most existing Lie group integrators rely on Magnus expansion of the…

Numerical Analysis · Mathematics 2026-05-07 Xi Wang , Victor Solo

In this paper, we consider a new approach for semi-discretization in time and spatial discretization of a class of semi-linear stochastic partial differential equations (SPDEs) with multiplicative noise. The drift term of the SPDEs is only…

Numerical Analysis · Mathematics 2023-07-10 Yukun Li , Liet Vo , Guanqian Wang

Symplectic integration methods based on operator splitting are well established in many branches of science. For Hamiltonian systems which split in more than two parts, symplectic methods of higher order have been studied in detail only for…

In this paper, we introduce a new simple approach to developing and establishing the convergence of splitting methods for a large class of stochastic differential equations (SDEs), including additive, diagonal and scalar noise types. The…

Numerical Analysis · Mathematics 2024-03-11 James Foster , Goncalo dos Reis , Calum Strange

We describe a way of solving a partial differential equation using the differential invariants of its point symmetries. By first solving its quotient PDE, which is given by the differential syzygies in the algebra of differential…

Differential Geometry · Mathematics 2020-05-15 Eivind Schneider

We present new splitting methods designed for the numerical integration of near-integrable Hamiltonian systems, and in particular for planetary N-body problems, when one is interested in very accurate results over a large time span. We…

Numerical Analysis · Mathematics 2015-04-10 Sergio Blanes , Fernando Casas , Ariadna Farres , Jacques Laskar , Joseba Makazaga , Ander Murua

We study a semilinear fractional-in-time Rayleigh-Stokes problem for a generalized second-grade fluid with a Lipschitz continuous nonlinear source term and initial data $u_0\in\dot{H}^\nu(\Omega)$, $\nu\in[0,2]$. We discuss stability of…

Numerical Analysis · Mathematics 2020-12-08 Mariam Al-Maskari , Samir Karaa

A bivariate spline method is developed to numerically solve second order elliptic partial differential equations (PDE) in non-divergence form. The existence, uniqueness, stability as well as approximation properties of the discretized…

Numerical Analysis · Mathematics 2017-01-05 Ming-Jun Lai , Chunmei Wang