Please use this identifier to cite or link to this item: https://doi.org/10.1137/S1064827501393253
DC FieldValue
dc.titleNumerical study of time-splitting spectral discretizations of nonlinear Schrödinger equations in the semiclassical regimes
dc.contributor.authorBao, W.
dc.contributor.authorJin, S.
dc.contributor.authorMarkowich, P.A.
dc.date.accessioned2014-10-28T03:12:20Z
dc.date.available2014-10-28T03:12:20Z
dc.date.issued2003-09
dc.identifier.citationBao, W., Jin, S., Markowich, P.A. (2003-09). Numerical study of time-splitting spectral discretizations of nonlinear Schrödinger equations in the semiclassical regimes. SIAM Journal on Scientific Computing 25 (1) : 27-64. ScholarBank@NUS Repository. https://doi.org/10.1137/S1064827501393253
dc.identifier.issn10648275
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104831
dc.description.abstractIn this paper we study the performance of time-splitting spectral approximations for general nonlinear Schrödinger equations (NLS) in the semiclassical regimes, where the Planck constant ε is small. The time-splitting spectral approximation under study is explicit, unconditionally stable and conserves the position density in L 1. Moreover it is time-transverse invariant and time-reversible when the corresponding NLS is. Extensive numerical tests are presented for weak/strong focusing/defocusing nonlinearities, for the Gross-Pitaevskii equation, and for current-relaxed quantum hydrodynamics. The tests are geared towards the understanding of admissible meshing strategies for obtaining "correct" physical observables in the semiclassical regimes. Furthermore, comparisons between the solutions of the NLS and its hydrodynamic semiclassical limit are presented.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1137/S1064827501393253
dc.sourceScopus
dc.subjectGross-Pitaevskii equation
dc.subjectMeshing strategy
dc.subjectNonlinear Schrödinger equation (NLS)
dc.subjectPhysical observable
dc.subjectSemiclassical regime
dc.subjectTime-splitting spectral approximation
dc.typeArticle
dc.contributor.departmentCOMPUTATIONAL SCIENCE
dc.description.doi10.1137/S1064827501393253
dc.description.sourcetitleSIAM Journal on Scientific Computing
dc.description.volume25
dc.description.issue1
dc.description.page27-64
dc.description.codenSJOCE
dc.identifier.isiut000186546800002
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