Convergence rates for dispersive approximation schemes to nonlinear Schrödinger equations

This article is devoted to the analysis of the convergence rates of several numerical approximation schemes for linear and nonlinear Schrödinger equations on the real line. Recently, the authors have introduced viscous and two-grid numerical approximation schemes that mimic at the discrete level the...

ver descrição completa

Detalhes bibliográficos
Autores: Ignat, L.I., Zuazua, E.
Tipo de documento: artigo
Estado:Versão publicada
Data de publicação:2012
País:España
Recursos:Basque Center for Applied Mathematics (BCAM)
Repositório:BIRD. BCAM's Institutional Repository Data
OAI Identifier:oai:bird.bcamath.org:20.500.11824/553
Acesso em linha:http://hdl.handle.net/20.500.11824/553
Access Level:Acceso aberto
Palavra-chave:Error analysis
Finite differences
Nonlinear Schrödinger equation
Strichartz estimates
Descrição
Resumo:This article is devoted to the analysis of the convergence rates of several numerical approximation schemes for linear and nonlinear Schrödinger equations on the real line. Recently, the authors have introduced viscous and two-grid numerical approximation schemes that mimic at the discrete level the so-called Strichartz dispersive estimates of the continuous Schrödinger equation. This allows to guarantee the convergence of numerical approximations for initial data in L2(R), a fact that cannot be proved in the nonlinear setting for standard conservative schemes unless more regularity of the initial data is assumed. In the present article we obtain explicit convergence rates and prove that dispersive schemes fulfilling the Strichartz estimates are better behaved for Hs(R) data if 0 < s< 1/2. Indeed, while dispersive schemes ensure a polynomial convergence rate, non-dispersive ones only yield logarithmic ones.