Title | ||
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Improved error estimates for splitting methods applied to highly-oscillatory nonlinear Schrödinger equations. |
Abstract | ||
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In this work, the error behavior of operator splitting methods is analyzed for highly-oscillatory differential equations. The scope of applications includes time-dependent nonlinear Schrodinger equations, where the evolution operator associated with the principal linear part is highly-oscillatory and periodic in time. In a first step, a known convergence result for the second-order Strang splitting method applied to the cubic Schrodinger equation is adapted to a wider class of nonlinearities. In a second step, the dependence of the global error on the decisive parameter 0 < epsilon << 1, defining the length of the period, is examined. The main result states that, compared to established error estimates, the Strang splitting method is more accurate by a factor e, provided that the time stepsize is chosen as an integer fraction of the period. This improved error behavior over a time interval of fixed length, which is independent of the period, is due to an averaging effect. The extension of the convergence result to higher-order splitting methods and numerical illustrations complement the investigations. |
Year | DOI | Venue |
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2016 | 10.1090/mcom/3088 | MATHEMATICS OF COMPUTATION |
Keywords | Field | DocType |
Highly-oscillatory differential equations,time-dependent nonlinear Schrodinger equations,operator splitting methods,Strang splitting method,error estimate,convergence result,averaging | Integer,Convergence (routing),Strang splitting,Differential equation,Mathematical optimization,Nonlinear system,Mathematical analysis,Schrödinger equation,Operator (computer programming),Periodic graph (geometry),Mathematics | Journal |
Volume | Issue | ISSN |
85 | 302 | 0025-5718 |
Citations | PageRank | References |
3 | 0.39 | 2 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
P. Chartier | 1 | 144 | 29.70 |
Florian Méhats | 2 | 80 | 14.01 |
Mechthild Thalhammer | 3 | 124 | 16.02 |
Yong Zhang | 4 | 29 | 4.56 |