Optimal error bounds on time-splitting methods for the nonlinear Schrödinger equation with low regularity potential and nonlinearity

Author:

Bao Weizhu1ORCID,Ma Ying2ORCID,Wang Chushan1ORCID

Affiliation:

1. Department of Mathematics, National University of Singapore, Singapore 119076, Singapore

2. Department of Mathematics, School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing 100124, P. R. China

Abstract

We establish optimal error bounds on time-splitting methods for the nonlinear Schrödinger equation with low regularity potential and typical power-type nonlinearity [Formula: see text], where [Formula: see text] is the density with [Formula: see text] the wave function and [Formula: see text] the exponent of the nonlinearity. For the first-order Lie–Trotter time-splitting method, optimal [Formula: see text]-norm error bound is proved for [Formula: see text]-potential and [Formula: see text], and optimal [Formula: see text]-norm error bound is obtained for [Formula: see text]-potential and [Formula: see text]. For the second-order Strang time-splitting method, optimal [Formula: see text]-norm error bound is established for [Formula: see text]-potential and [Formula: see text], and optimal [Formula: see text]-norm error bound is proved for [Formula: see text]-potential and [Formula: see text] (or [Formula: see text]). Compared to those error estimates of time-splitting methods in the literature, our optimal error bounds either improve the convergence rates under the same regularity assumptions or significantly relax the regularity requirements on potential and nonlinearity for optimal convergence orders. A key ingredient in our proof is to adopt a new technique called regularity compensation oscillation (RCO), where low frequency modes are analyzed by phase cancellation, and high frequency modes are estimated by regularity of the solution. Extensive numerical results are reported to confirm our error estimates and to demonstrate that they are sharp.

Funder

Ministry of Education of Singapore

Publisher

World Scientific Pub Co Pte Ltd

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3