<p>Owing to the inclusion of a small parameter (i.e., <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10092_2025_636_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="75" /> </InlineMediaObject> <EquationSource Format="TEX">\(0&lt;\varepsilon \ll {1}\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>0</mn> <mo>&lt;</mo> <mi>ε</mi> <mo>≪</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation>) in the wave operator and initial velocity, the solution of the nonlinear Schrödinger equation with wave operator (NLSW) exhibits high oscillation in time, thereby posing significant challenges in constructing high-resolution numerical methods and establishing the uniform error estimates for the proposed methods. This paper introduces two novel exponential wave integrator Fourier pseudo-spectral methods (one is two-level implicit and time reversible, the other is three-level explicit) for solving the periodic boundary-initial value problem of the NLSW. A concise analysis establishes the uniform error estimates. Numerical experiments validate the uniform error estimates and efficiency of these two methods.</p>

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Convergence study of two exponential wave integrator Fourier pseudo-spectral methods for the nonlinear Schrödinger equation with wave operator

  • Yue Cheng,
  • Tingchun Wang

摘要

Owing to the inclusion of a small parameter (i.e., \(0<\varepsilon \ll {1}\) 0 < ε 1 ) in the wave operator and initial velocity, the solution of the nonlinear Schrödinger equation with wave operator (NLSW) exhibits high oscillation in time, thereby posing significant challenges in constructing high-resolution numerical methods and establishing the uniform error estimates for the proposed methods. This paper introduces two novel exponential wave integrator Fourier pseudo-spectral methods (one is two-level implicit and time reversible, the other is three-level explicit) for solving the periodic boundary-initial value problem of the NLSW. A concise analysis establishes the uniform error estimates. Numerical experiments validate the uniform error estimates and efficiency of these two methods.