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The aim of this work is to provide the strong convergence results of numerical approximations of a general second order non-autonomous semilinear stochastic partial differential equation (SPDE) driven simultaneously by an additive…

Numerical Analysis · Mathematics 2024-09-11 Aurelien Junior Noupelah , Jean Daniel Mukam , Antoine Tambue

This work is concerned with existence of weak solutions to discon- tinuous stochastic differential equations driven by multiplicative Gaus- sian noise and sliding mode control dynamics generated by stochastic differential equations with…

Optimization and Control · Mathematics 2015-04-27 Viorel Barbu , Stefano Bonaccorsi , Luciano Tubaro

We consider the explicit numerical approximations of stochastic differential equations (SDEs) driven by Brownian process and Poisson jump. It is well known that under non-global Lipschitz condition, Euler Explicit method fails to converge…

Numerical Analysis · Mathematics 2018-02-21 Antoine Tambue , Jean Daniel Mukam

In this work, we present an efficient approach to solve nonlinear high-contrast multiscale diffusion problems. We incorporate the explicit-implicit-null (EIN) method to separate the nonlinear term into a linear term and a damping term, and…

Numerical Analysis · Mathematics 2024-03-22 Yating Wang , Wing Tat Leung

In this paper, we derive a strong convergence rate of spatial finite difference approximations for both focusing and defocusing stochastic cubic Schr\"odinger equations driven by a multiplicative $Q$-Wiener process. Beyond the uniform…

Probability · Mathematics 2017-03-29 Jianbo Cui , Jialin Hong , Zhihui Liu

Approximate resolution of linear systems of differential equations with varying coefficients is a recurrent problem shared by a number of scientific and engineering areas, ranging from Quantum Mechanics to Control Theory. When formulated in…

Mathematical Physics · Physics 2009-04-11 S. Blanes , F. Casas , J. A. Oteo , J. Ros

Model predictive control is an advanced control approach for multivariable systems with constraints, which is reliant on an accurate dynamic model. Most real dynamic models are however affected by uncertainties, which can lead to…

Optimization and Control · Mathematics 2021-03-10 E. Bradford , L. Imsland

We show that symplectic and linearly-implicit integrators proposed by [Zhang and Skeel, 1997] are variational linearizations of Newmark methods. When used in conjunction with penalty methods (i.e., methods that replace constraints by stiff…

Numerical Analysis · Mathematics 2014-12-08 Molei Tao , Houman Owhadi

In a recent paper we presented a new ultra efficient numerical method for solving kinetic equations of the Boltzmann type (G. Dimarco, R. Loubere, Towards an ultra efficient kinetic scheme. Part I: basics on the 689 BGK equation, J. Comp.…

Numerical Analysis · Mathematics 2015-06-12 Giacomo Dimarco , Raphaël Loubere

Stochastic differential equations (SDEs) offer powerful and accessible mathematical models for capturing both deterministic and probabilistic aspects of dynamic behavior across a wide range of physical, financial, and social systems.…

Statistics Theory · Mathematics 2026-02-17 Paromita Banerjee , Anirban Mondal

We aim to solve a structured convex optimization problem, where a nonsmooth function is composed with a linear operator. When opting for full splitting schemes, usually, primal-dual type methods are employed as they are effective and also…

Optimization and Control · Mathematics 2019-05-17 Radu Ioan Bot , Axel Böhm

In this paper we develop a novel, discrete-time optimal control framework for mechanical systems with uncertain model parameters. We consider finite-horizon problems where the performance index depends on the statistical moments of the…

Optimization and Control · Mathematics 2017-05-17 George I. Boutselis , Yunpeng Pan , Gerardo De La Tore , Evangelos A. Theodorou

This paper presents a perturbation analysis framework for nonsmooth optimization on connected Riemannian manifolds to bridge the gap between the rapid development of algorithmic approaches and a robust theoretical foundation. Using…

Optimization and Control · Mathematics 2025-10-01 Yuexin Zhou , Chao Ding , Yangjing Zhang

We develop and analyze a general class of Euler-type numerical schemes for Levy-driven McKean-Vlasov stochastic differential equations (SDEs), where the drift, diffusion and jump coefficients grow super-linearly in the state variable. These…

Numerical Analysis · Mathematics 2025-09-12 Jingtao Zhu , Yuying Zhao , Siqing Gan

The work is devoted to the development of numerical methods for computing "formal solutions" of interval systems of linear algebraic equations. These solutions are found in Kaucher interval arithmetic, which extends and completes the…

Numerical Analysis · Mathematics 2019-03-26 Sergey P. Shary

We develop in this work a numerical method for stochastic differential equations (SDEs) with weak second order accuracy based on Gaussian mixture. Unlike the conventional higher order schemes for SDEs based on It\^o-Taylor expansion and…

Numerical Analysis · Mathematics 2021-08-12 Lei Li , Jianfeng Lu , Jonathan Mattingly , Lihan Wang

We uncover a combinatorial structure governing the differential equations satisfied by wavefunction coefficients of scalar fields with generic masses in de Sitter space. Using an integral representation of the massive mode functions, we…

High Energy Physics - Theory · Physics 2026-04-13 Daniel Baumann , Austin Joyce , Hayden Lee , Kamran Salehi Vaziri

We derive and analyze numerical methods for underdamped (kinetic) Langevin dynamics in a domain with elastic reflection at the boundary. First-order approximations are based on an Euler-type scheme incorporating collision-handling at the…

Numerical Analysis · Mathematics 2025-12-10 B. Leimkuhler , A. Sharma , M. V. Tretyakov

In this paper, we study numerical methods for the homogenization of linear second-order elliptic equations in nondivergence-form with periodic diffusion coefficients and large drift terms. Upon noting that the effective diffusion matrix can…

Numerical Analysis · Mathematics 2025-06-18 Timo Sprekeler , Han Wu , Zhiwen Zhang

In this study, we investigate a vector-valued Witsenhausen model where the second decision maker (DM) acquires a vector of observations before selecting a vector of estimations. Here, the first DM acts causally whereas the second DM…

Optimization and Control · Mathematics 2024-08-26 Mengyuan Zhao , Tobias J. Oechtering , Maël Le Treust