Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications

In this paper, we present a novel Galerkin spectral method for numerically solving the stochastic nonlinear Schrödinger (NLS) equation driven by multivariate Gaussian random variables, including the nonlinear term. Our approach involves deriving the tensor product of triple random orthogonal basis a...

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Main Author: Hongling Xie
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2023/8007384
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author Hongling Xie
author_facet Hongling Xie
author_sort Hongling Xie
collection DOAJ
description In this paper, we present a novel Galerkin spectral method for numerically solving the stochastic nonlinear Schrödinger (NLS) equation driven by multivariate Gaussian random variables, including the nonlinear term. Our approach involves deriving the tensor product of triple random orthogonal basis and random functions, which enables us to effectively handle the stochasticity and nonlinear term in the equation. We apply this newly proposed method to solve both one- and two-dimensional stochastic NLS equations, providing detailed analysis and comparing the results with Monte Carlo simulation. In addition, the proposed method is applied to the stochastic Ginzburg–Landau equation. Our method exhibits excellent performance in both spatial and random spaces, achieving spectral accuracy in the numerical solutions.
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institution Kabale University
issn 2314-4785
language English
publishDate 2023-01-01
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spelling doaj-art-2cb63537adda4311807d4332a125bd6f2025-02-03T06:47:41ZengWileyJournal of Mathematics2314-47852023-01-01202310.1155/2023/8007384Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and ApplicationsHongling Xie0School of Mathematics and StatisticsIn this paper, we present a novel Galerkin spectral method for numerically solving the stochastic nonlinear Schrödinger (NLS) equation driven by multivariate Gaussian random variables, including the nonlinear term. Our approach involves deriving the tensor product of triple random orthogonal basis and random functions, which enables us to effectively handle the stochasticity and nonlinear term in the equation. We apply this newly proposed method to solve both one- and two-dimensional stochastic NLS equations, providing detailed analysis and comparing the results with Monte Carlo simulation. In addition, the proposed method is applied to the stochastic Ginzburg–Landau equation. Our method exhibits excellent performance in both spatial and random spaces, achieving spectral accuracy in the numerical solutions.http://dx.doi.org/10.1155/2023/8007384
spellingShingle Hongling Xie
Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications
Journal of Mathematics
title Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications
title_full Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications
title_fullStr Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications
title_full_unstemmed Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications
title_short Numerical Method for Stochastic Nonlinear Schrödinger Equation Driven by Multivariate Gaussian Measure: Algorithms and Applications
title_sort numerical method for stochastic nonlinear schrodinger equation driven by multivariate gaussian measure algorithms and applications
url http://dx.doi.org/10.1155/2023/8007384
work_keys_str_mv AT honglingxie numericalmethodforstochasticnonlinearschrodingerequationdrivenbymultivariategaussianmeasurealgorithmsandapplications