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We investigate the existence and local uniqueness of normalized $k$-peak solutions for the fractional Schr\"odinger equations with attractive interactions with a class of degenerated trapping potential with non-isolated critical points.…

Analysis of PDEs · Mathematics 2021-05-06 Qing Guo , Peng Luo , Chunhua Wang , Jing Yang

The filtered Lie splitting scheme is an established method for the numerical integration of the periodic nonlinear Schr\"{o}dinger equation at low regularity. Its temporal convergence was recently analyzed in a framework of discrete…

Numerical Analysis · Mathematics 2025-11-19 Lun Ji , Alexander Ostermann

Finite difference approximation, in addition to Taylor truncation errors, introduces numerical dispersion-and-dissipation errors into numerical solutions of partial differential equations. We analyze a class of finite difference schemes…

Numerical Analysis · Mathematics 2014-09-12 Yi-Hung Kuo , Long Lee , Gregory Lyng

In this paper, we propose two time-splitting finite element methods to solve the semiclassical nonlinear Schr\"odinger equation (NLSE) with random potentials. We then introduce the multiscale finite element method (MsFEM) to reduce the…

Numerical Analysis · Mathematics 2025-02-12 Panchi Li , Zhiwen Zhang

In this paper we prove the convergence of a Crank-Nicolson type Galerkin finite element scheme for the initial value problem associated to the Benjamin-Ono equation. The proof is based on a recent result for a similar discrete scheme for…

Numerical Analysis · Mathematics 2021-04-23 Sondre Tesdal Galtung

An estimation problem of fundamental interest is that of phase synchronization, in which the goal is to recover a collection of phases using noisy measurements of relative phases. It is known that in the Gaussian noise setting, the maximum…

Optimization and Control · Mathematics 2016-11-02 Huikang Liu , Man-Chung Yue , Anthony Man-Cho So

In this paper, we propose a conservative local discontinuous Galerkin method for one-dimensional nonlinear Schr\"odinger equation. By using special upwind-biased numerical fluxes, we establish the optimal rate of convergence $\mathcal…

Numerical Analysis · Mathematics 2019-02-25 Jialin Hong , Lihai Ji , Zhihui Liu

This paper develops three high-order accurate discontinuous Galerkin (DG) methods for the one-dimensional (1D) and two-dimensional (2D) nonlinear Dirac (NLD) equations with a general scalar self-interaction. They are the Runge-Kutta DG…

Numerical Analysis · Mathematics 2020-11-03 Shu-Cun Li , Huazhong Tang

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

This paper introduces a discretization-accurate stopping criterion of symmetric iterative methods for solving systems of algebraic equations resulting from the finite element approximation. The stopping criterion consists of the evaluations…

Numerical Analysis · Mathematics 2019-09-19 Zhiqiang Cai , Shuhao Cao , Robert D. Falgout

This paper presents a new narrow-stencil finite difference method for approximating the viscosity solution of second order fully nonlinear elliptic partial differential equations including Hamilton-Jacobi-Bellman equations. The proposed…

Numerical Analysis · Mathematics 2019-10-30 Xiaobing Feng , Thomas Lewis

We introduce a new approach for designing numerical schemes for stochastic differential equations (SDEs). The approach, which we have called direction and norm decomposition method, proposes to approximate the required solution $X_t$ by…

Numerical Analysis · Mathematics 2017-02-21 C. M. Mora , H. A. Mardones , J. C. Jimenez , M. Selva , R. Biscay

We propose a continuous-time formulation of persistent contrastive divergence (PCD) for maximum likelihood estimation (MLE) of unnormalised densities. Our approach expresses PCD as a coupled, multiscale system of stochastic differential…

Machine Learning · Statistics 2025-10-03 Paul Felix Valsecchi Oliva , O. Deniz Akyildiz , Andrew Duncan

This article focuses on an energy-conservation Galerkin finite element method (FEM) for the generalized Klein-Gordon-Zakharov (KGZ) equations. This method combines the bilinear finite element method for spatial discretization with the…

Numerical Analysis · Mathematics 2026-05-13 Xuemiao Xu , Maosheng Jiang , Jiansong Zhang , Jiang Zhu

A time-stepping $L1$ scheme for solving a time fractional Fokker-Planck equation of order $\alpha \in (0, 1)$, with a general driving force, is investigated. A stability bound for the semi-discrete solution is obtained for…

Numerical Analysis · Mathematics 2021-06-29 Kassem Mustapha , Omar M. Knio , Olivier P. Le Maître

The present work introduces and investigates an explicit time discretization scheme, called the projected Euler method,to numerically approximate random periodic solutions of semi-linear SDEs under non-globally Lipschitz conditions. The…

Numerical Analysis · Mathematics 2024-11-26 Yujia Guo , Xiaojie Wang , Yue Wu

An initial-boundary value problem for the $n$-dimensional ($n\geq 2$) time-dependent Schr\"odinger equation in a semi-infinite (or infinite) parallelepiped is considered. Starting from the Numerov-Crank-Nicolson finite-difference scheme, we…

Numerical Analysis · Mathematics 2026-01-05 Bernard Ducomet , Alexander Zlotnik , Alla Romanova

This paper is concerned with the adaptive numerical treatment of stochastic partial differential equations. Our method of choice is Rothe's method. We use the implicit Euler scheme for the time discretization. Consequently, in each step, an…

Semidefinite programming (SDP) is a powerful tool for tackling a wide range of computationally hard problems such as clustering. Despite the high accuracy, semidefinite programs are often too slow in practice with poor scalability on large…

Machine Learning · Statistics 2022-02-10 Yubo Zhuang , Xiaohui Chen , Yun Yang

In this article we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice,…

Computation · Statistics 2017-02-07 Alexandros Beskos , Ajay Jasra , Kody Law , Raul Tempone , Yan Zhou
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