A Numerical Approach for (2+1)D Saturable Nonlinear Schrödinger Equations With Generalized Loss

ABSTRACT This paper details a standard Crank‐Nicolson finite difference (CNFD) discretization for the ()D nonlinear Schrödinger equation with saturable nonlinearity and a generalized loss. This study establishes the fundamental properties of the numerical scheme, including the boundedness, existence, and uniqueness of its discrete solution. A generalized approach is introduced to derive error estimates, specifically for the boundedness of the discrete norm. These estimates are subsequently employed to rigorously prove the optimal second‐order convergence of the numerical solution in both the discrete and norms. The theoretical claims are verified through a series of illustrative numerical experiments.

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Journal
Numerical Methods for Partial Differential Equations
Published
2026-07-01
DOI
https://doi.org/10.1002/num.70121
Primary Topic
Numerical methods for differential equations
Type
article
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article

A Numerical Approach for (2+1)D Saturable Nonlinear Schrödinger Equations With Generalized Loss

Auméés Le, Le Khanh Huy
Numerical Methods for Partial Differential Equations
Numerical methods for differential equations
article

A Numerical Approach for (2+1)D Saturable Nonlinear Schrödinger Equations With Generalized Loss

Auméés Le, Le Khanh Huy
article en

Abstract

ABSTRACT This paper details a standard Crank‐Nicolson finite difference (CNFD) discretization for the ()D nonlinear Schrödinger equation with saturable nonlinearity and a generalized loss. This study establishes the fundamental properties of the numerical scheme, including the boundedness, existence, and uniqueness of its discrete solution. A generalized approach is introduced to derive error estimates, specifically for the boundedness of the discrete norm. These estimates are subsequently employed to rigorously prove the optimal second‐order convergence of the numerical solution in both the discrete and norms. The theoretical claims are verified through a series of illustrative numerical experiments.

Numerical Methods for Partial Differential EquationsVol. 42(4)
Vietnam National University Ho Chi Minh City (VN), Ho Chi Minh City University of Science (VN)
Reduced inequalities
Openalex Percentile: Top 5%
Numerical methods for differential equations
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