Split-step methods for the solution of the nonlinear Schro¨dinger equation
SIAM Journal on Numerical Analysis
Geometric integrators for the nonlinear Schrödinger equation
Journal of Computational Physics
Exponential time differencing for stiff systems
Journal of Computational Physics
Practical symplectic partitioned Runge--Kutta and Runge--Kutta--Nyström methods
Journal of Computational and Applied Mathematics
On the preservation of phase space structure under multisymplectic discretization
Journal of Computational Physics
Explicit Exponential Runge-Kutta Methods for Semilinear Parabolic Problems
SIAM Journal on Numerical Analysis
B-series and Order Conditions for Exponential Integrators
SIAM Journal on Numerical Analysis
EXPINT---A MATLAB package for exponential integrators
ACM Transactions on Mathematical Software (TOMS)
An error analysis of the modified scaling and squaring method
Computers & Mathematics with Applications
The scaling and modified squaring method for matrix functions related to the exponential
Applied Numerical Mathematics
Exponential Runge--Kutta methods for the Schrödinger equation
Applied Numerical Mathematics
Fourth Order Time-Stepping for Kadomtsev-Petviashvili and Davey-Stewartson Equations
SIAM Journal on Scientific Computing
Hi-index | 31.45 |
The cubic nonlinear Schrodinger (NLS) equation with periodic boundary conditions is solvable using Inverse Spectral Theory. The ''nonlinear'' spectrum of the associated Lax pair reveals topological properties of the NLS phase space that are difficult to assess by other means. In this paper we use the invariance of the nonlinear spectrum to examine the long time behavior of exponential and multisymplectic integrators as compared with the most commonly used split step approach. The initial condition used is a perturbation of the unstable plane wave solution, which is difficult to numerically resolve. Our findings indicate that the exponential integrators from the viewpoint of efficiency and speed have an edge over split step, while a lower order multisymplectic is not as accurate and too slow to compete.