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In this paper, we focus on numerical approximations of Piecewise Diffusion Markov Processes (PDifMPs), particularly when the explicit flow maps are unavailable. Our approach is based on the thinning method for modelling the jump mechanism…

Numerical Analysis · Mathematics 2024-08-23 Evelyn Buckwar , Amira Meddah

In this paper, a non-uniform time-stepping convex-splitting numerical algorithm for solving the widely used time-fractional Cahn-Hilliard equation is introduced. The proposed numerical scheme employs the $L1^+$ formula for discretizing the…

Numerical Analysis · Mathematics 2020-06-04 Jun Zhang , Jia Zhao , JinRong Wang

We study the Strang splitting scheme for quasilinear Schr\"odinger equations. We establish the convergence of the scheme for solutions with small initial data. We analyze the linear instability of the numerical scheme, which explains the…

Numerical Analysis · Mathematics 2014-09-22 Jianfeng Lu , Jeremy L. Marzuola

This article is devoted to the construction of new numerical methods for the semiclassical Schr\"odinger equation. A phase-amplitude reformulation of the equation is described where the Planck constant epsilon is not a singular parameter.…

Analysis of PDEs · Mathematics 2018-10-15 Philippe Chartier , Loïc Le Treust , Florian Méhats

As a classical time-stepping method, it is well-known that the Strang splitting method reaches the first-order accuracy by losing two spatial derivatives. In this paper, we propose a modified splitting method for the 1D cubic nonlinear…

Numerical Analysis · Mathematics 2022-12-20 Yifei Wu

The law of the iterated logarithm (LIL) for the time-homogeneous Markov process with a unique invariant measure characterizes the almost sure maximum possible fluctuation of time averages around the ergodic limit. Whether a numerical…

Numerical Analysis · Mathematics 2025-11-10 Chuchu Chen , Xinyu Chen , Jialin Hong

We consider the numerical solution of Hamilton-Jacobi-Bellman equations arising in stochastic control theory. We introduce a class of monotone approximation schemes relying on monotone interpolation. These schemes converge under very weak…

Numerical Analysis · Mathematics 2014-05-26 Kristian Debrabant , Espen R. Jakobsen

Suppose we observe a trajectory of length $n$ from an exponentially $\alpha$-mixing stochastic process over a finite but potentially large state space. We consider the problem of estimating the probability mass placed by the stationary…

Machine Learning · Statistics 2025-06-09 Milind Nakul , Vidya Muthukumar , Ashwin Pananjady

A linear optics-based scheme to implement various quantum information processing tasks is of paramount importance due to ease of implementation and low noise. Many information-theoretic tasks depend on the successful discrimination of Bell…

Quantum Physics · Physics 2024-02-02 Jatin Ghai , Sibasish Ghosh

We propose a new convergent time semi-discrete scheme for the stochastic Landau-Lifshitz-Gilbert equation. The scheme is only linearly implicit and does not require the resolution of a nonlinear problem at each time step. Using a martingale…

Analysis of PDEs · Mathematics 2014-03-13 François Alouges , Anne De Bouard , Antoine Hocquet

We consider the propagation of temporally incoherent waves in multimode optical fibers (MMFs) in the framework of the multimode nonlinear Schr\"odinger (NLS) equation accounting for the impact of the natural structural disorder that affects…

Many problems in navigation and tracking require increasingly accurate characterizations of the evolution of uncertainty in nonlinear systems. Nonlinear uncertainty propagation approaches based on Gaussian mixture density approximations…

Machine Learning · Statistics 2025-12-30 Jackson Kulik , Keith A. LeGrand

This article deals with the spatio-temporal sensors deployment in order to maximize detection probability of an intelligent and randomly moving target in an area under surveillance. Our work is based on the rare events simulation framework.…

Neural and Evolutionary Computing · Computer Science 2017-02-24 Chouchane Mathieu , Paris Sébastien , Le Gland François , Ouladsine Mustapha

The aim of this paper is to develop a general method for constructing approximation schemes for viscosity solutions of fully nonlinear pathwise stochastic partial differential equations, and for proving their convergence. Our results apply…

Analysis of PDEs · Mathematics 2019-11-01 Benjamin Seeger

We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

Probability · Mathematics 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva

A special type of binomial splitting process is studied. Such a process can be used to model a high-dimensional corner parking problem, as well as the depth of random PATRICIA tries (a special class of digital tree data structures). The…

Probability · Mathematics 2013-11-27 Michael Fuchs , Hsien-Kuei Hwang , Yoshiaki Itoh , Hosam H. Mahmoud

This paper establishes the convergence of a time-steeping scheme for time fractional diffusion problems with nonsmooth data. We first analyze the regularity of the model problem with nonsmooth data, and then prove that the time-steeping…

Numerical Analysis · Mathematics 2018-04-30 Binjie Li , Hao Luo , Xiaoping Xie

In this work, we consider the coupled systems of linear unsteady partial differential equations, which arise in the modeling of poroelasticity processes. Stability estimates of weighted difference schemes for the coupled system of equations…

Numerical Analysis · Computer Science 2013-11-18 A. E. Kolesov , P. N. Vabishchevich , M. V. Vasilyeva

We introduce a stochastic version of the cutting-plane method for a large class of data-driven Mixed-Integer Nonlinear Optimization (MINLO) problems. We show that under very weak assumptions the stochastic algorithm is able to converge to…

Optimization and Control · Mathematics 2021-03-04 Dimitris Bertsimas , Michael Lingzhi Li

We extend the branching process based numerical algorithm of Bouchard et al. [3], that is dedicated to semilinear PDEs (or BSDEs) with Lipschitz nonlinearity, to the case where the nonlinearity involves the gradient of the solution. As in…

Probability · Mathematics 2017-10-31 Bruno Bouchard , Xiaolu Tan , Xavier Warin
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