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Lattice Boltzmann schemes for the nonlinear Schrödinger equation
Linhao Zhong1, Shide Feng, Ping Dong
1Laboratory of Cloud-Precipitation Physics and Severe Storms (LACS), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China. zlh@mail.iap.ac.cn
The lattice Boltzmann (LB) method accurately solves the nonlinear Schrödinger (NLS) equation. New LB schemes and initial conditions reduce errors, offering a superior alternative to traditional finite difference methods for NLS problems.
Area of Science:
- Computational physics
- Numerical analysis
- Quantum mechanics
Background:
- The nonlinear Schrödinger (NLS) equation models various physical phenomena.
- Solving the time-dependent NLS equation numerically presents challenges in accuracy and efficiency.
- Existing methods like finite difference schemes have limitations.
Purpose of the Study:
- To apply the lattice Boltzmann (LB) method for solving the time-dependent cubic NLS equation.
- To develop and evaluate novel LB schemes with improved accuracy for reaction terms.
- To introduce an LB initial condition enhancing numerical stability and precision.
Main Methods:
- Construction of three diffusion-reaction LB schemes with varying reaction term approximation orders.
- Implementation of a novel LB initial condition incorporating the first-order nonequilibrium distribution function.
- Application of these schemes to simulate one-soliton propagation and homoclinic orbit problems.
Main Results:
- The proposed LB schemes effectively solve the cubic NLS equation.
- High-order approximation of the reaction term and the new LB initial condition significantly reduce truncation errors.
- LB method demonstrates comparable or superior accuracy to the Crank-Nicolson finite difference scheme.
Conclusions:
- The developed LB schemes provide an accurate and efficient approach for the cubic NLS equation.
- The LB method offers a promising alternative for simulating complex NLS problems.
- The study highlights the effectiveness of advanced LB techniques in computational physics.
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