A new error analysis of a linearized Euler Galerkin scheme for Schrödinger equation with cubic nonlinearity

In this paper, a linearized Euler Galerkin scheme is studied and the unconditionally optimal error estimate in L 2 -norm is obtained for Schrödinger equation with cubic nonlinearity without any time-step restriction. The key to the analysis is to bound the H 1 -norm between the numerical solution and the Ritz projection of the exact solution by mathematical induction for two cases rather than the error splitting technique used in the previous work. Finally, some numerical results are presented to confirm the theoretical analysis.

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Publication Details

Journal
Applied Mathematics Letters
Published
2024-11-25
DOI
https://doi.org/10.1016/j.aml.2024.109401
Citations
2
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
1.46

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article

A new error analysis of a linearized Euler Galerkin scheme for Schrödinger equation with cubic nonlinearity

Huaijun Yang
2 citations
Applied Mathematics Letters
Numerical methods for differential equations
1.46
article

A new error analysis of a linearized Euler Galerkin scheme for Schrödinger equation with cubic nonlinearity

Huaijun Yang
article en
2 citations

Abstract

In this paper, a linearized Euler Galerkin scheme is studied and the unconditionally optimal error estimate in L 2 -norm is obtained for Schrödinger equation with cubic nonlinearity without any time-step restriction. The key to the analysis is to bound the H 1 -norm between the numerical solution and the Ritz projection of the exact solution by mathematical induction for two cases rather than the error splitting technique used in the previous work. Finally, some numerical results are presented to confirm the theoretical analysis.

Applied Mathematics LettersVol. 162
Zhengzhou University of Aeronautics (CN)
National Natural Science Foundation of China, Key Scientific Research Project of Colleges and Universities in Henan Province
Openalex Percentile: Top 17%
Numerical methods for differential equations
1.46
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